This study examines the asymmetric and state-dependent effects of exchange rate movements on money demand in six developed economies (Australia, Canada, the Euro Area, Japan, the United Kingdom, and the United States) using quarterly data from 1970Q1 to 2025Q1. Linear ARDL and nonlinear ARDL (NARDL) models are employed alongside quantile ARDL (QARDL) to capture asymmetry and distributional heterogeneity. The ARDL results confirm a stable long-run relationship between money demand and its determinants, while NARDL estimates reveal pronounced asymmetries between appreciations and depreciations, consistent with patterns attributable to substitution and wealth effects. These effects are stronger and more consistent for M3 than M1, reflecting broader portfolio adjustments. Quantile results indicate that exchange rate effects are highly state-dependent, intensifying at the tails of the distribution. Overall, the findings highlight the importance of nonlinear, state-dependent modeling and the relevance of broad money aggregates in monetary policy analysis.
Climate policy uncertainty (CPU) has been characterized by abrupt shocks in the US economy for at least two decades. Consequently, CPU influences investment decisions, especially in the energy markets. Motivated by the discussion related to climate change, energy security, and energy price volatility, it is inevitable to explore whether CPU influences the energy sector. Although the current literature in energy economics mainly investigates the impact of CPU on energy consumption, empirical evidence is scant on the influence of CPU on energy production. Filling this imperative research lacuna, this study investigates whether CPU affects total (TEP), non-renewable (NREP), and renewable energy production (REP) in the US. This study adopts a recently developed machine learning methodology (i.e., Quantile-on-Quantile Kernel Regularized Least Squares approach) for robust results across quantiles. The key findings document that the CPU is responsible for an upsurge in TEP, NREP, and REP across the quantiles. The study suggests a foreseeable and sustainable climate policy framework, such as long-term renewable subsidies and explicit fossil-fuel phase-out plans, to avoid distortions in the US energy industry that are caused by uncertainty.
As corruption drains $3.6 trillion annually from the global economy, researchers explore the association between gender dynamics, women's empowerment, and corruption. While existing literature presents mixed evidence on women's anti-corruption influence, both trait-based and institutional perspectives often assume simplified linear relationships. This study examines the non-linear association between women's empowerment across civil, political, and social spheres and corruption, accounting for political and economic contexts. Using panel data from 92 countries over two decades and employing a dynamic panel threshold model, we find that women's political empowerment exhibits non-linear and context-dependent patterns, notably in Asia, low-income countries, and across different gender representation categories. Our analysis uncovers thresholds beyond which the negative association with corruption strengthens, consistent with critical mass theory, while some countries experience temporal shifts in their empowerment levels. Following Tertilt et al. (2022), we identify two transmission channels-bargaining and public policy-that help explain the institutional mechanisms underlying these non-linear patterns. These findings highlight the importance of sustained empowerment over symbolic inclusion, offering insights into gender-based institutional reforms and corruption reduction strategies.
African economies are particularly vulnerable to macroeconomic volatility due to structural fragilities, external commodity dependence, and weak policy buffers. This study investigates the pass-through of macroeconomic shocks and their implications for income growth in 15 designated African economies from 2000 to 2024, using a Panel Vector Auto regression (PVAR) and a Panel Structural VAR framework implemented in Python and R Studio; for the PSVAR, we increased the periodicity from 1990 to 2023 using R studio. By integrating time-series dynamics with cross-sectional interdependencies, the PVAR approach provides a robust platform for disentangling the complex interactions among key variables such as GDP growth, inflation, exchange rates, and GDP per capita growth. Using the PSVAR, we estimated two scenarios of an increase and a decrease in growth. We found that a progressive shock to GDP growth brings about a preliminary increase in inflation, and the exchange rate declined from the inflation shock, which leads to depreciation of the currency against the dollar. GDP per capita increased from the shock of the exchange rate. Additionally, a negative shock to GDP growth brings about a decline in GDP; this shock tends to lead to a decline in inflation. The shock from inflation led to an increase in the exchange rate, which can be attributed to the rise in exchange rates resulting from monetary policies. GDP per capita declined from the exchange rate shock. This means an increase in GDP growth leads to a rise in inflation, a reduction in exchange rate, and an upsurge in GDP per capita, while a decline in GDP growth brings about a decrease in inflation, a rise in exchange rate, and a fall in GDP per capita. This paper recommends that policymakers in African economies should strengthen exchange rate management and build policy buffers to alleviate the unfavorable impact of inflation and external shocks on income growth. Secondly, given the dominant influence of exchange rate and inflation on GDP per capita, coordinated monetary and fiscal policies are essential to ensure macroeconomic stability and sustained income growth.
Purpose —This study addresses the longstanding debate concerning the relationship between Environmental, Social, and Governance (ESG) engagement and financial performance within the banking industry by systematically synthesizing the existing empirical evidence. Design/Methodology/Approach —A comprehensive literature review identified 28 peer-reviewed studies, yielding 194 distinct effect sizes. Employing a three-level random-effects meta-analytic framework, we estimate the overall ESG-performance association besides ESG subdimensions (E, S, G), and examine key moderating factors, including data sources, financial performance measures, and the macro-regulatory period (pre- versus post-Paris Agreement). Findings —The results indicate a small yet statistically significant positive association between ESG engagement and banking financial performance. The environmental pillar exhibits a consistent positive relationship, whereas the social and governance dimensions do not demonstrate statistically significant independent effects. Return on equity appears more sensitive to ESG variation relative to alternative performance indicators. Additionally, discrepancies across ESG rating providers reveal meaningful measurement heterogeneity. Temporal analysis further suggests that the ESG–performance association strengthened in the post-Paris Agreement regulatory period. The findings remain robust to publication-bias diagnostics. Originality/Value —While corroborating evidence from broader corporate ESG research, this study represents, to our knowledge, the first meta-analysis focused exclusively on the banking sector. Methodologically, it demonstrates the advantages of a three-level meta-analytic framework for addressing statistical dependencies among multiple effect sizes derived from individual primary studies. By decomposing aggregate ESG into its environmental, social, and governance components, evaluating the moderating role of alternative financial metrics (ROA, ROE, and Tobin’s Q), assessing divergence across data providers, and incorporating a temporal analysis of the regulatory shift following the 2015 Paris Agreement, this study advances the literature and offers policy-relevant implications for scholars, practitioners, and regulators.
This study uses a panel smooth transition regression (PSTR) framework and a novel measure of business cycle (BC) to document regime-dependent, non-linear dynamics in funding liquidity, a relationship that existing linear studies have not captured but that is beneficial for countercyclical macroprudential policy calibration. Employing PSTR framework on quarterly data of U.S. bank holding companies from 1990Q1 to 2021Q4 and the business cycle index of Brave et al. (2019), we document strong evidence of nonlinear dynamics in the relationship between BC conditions and funding liquidity risk. Specifically, the BC exerts a negative and statistically significant effect on funding liquidity risk, indicating that banks tend to build capital buffers and adopt more conservative funding strategies during economic downturns, while expanding lending activity during economic upswings. In contrast, financial crisis episodes are associated with a positive effect on funding liquidity, consistent with the flight-to-safety (or flight-to-capital) hypothesis, whereby depositors reallocate funds toward relatively safer bank deposits during periods of higher uncertainty. These findings underscore the role of BC index's thresholds in liquidity dynamics and suggest that policymakers and bank supervisors incorporate nonlinear macro-financial effects when designing countercyclical liquidity and bailout measures to ease banks' funding constraints during stress periods. The study has important implications for bank managers in terms of adjusting funding liquidity buffers and risk-taking across BC regimes.
This study investigates the influence of weather conditions, including temperature, wind speed, humidity, and precipitation, on financial market performance in France, with a particular focus on the renewable energy sector. To this end, we construct a new French Renewable Energy Financial Index (REFI) that aggregates listed companies involved in renewable energy production and distribution across multiple industries. The REFI introduces an original benchmark that enables a comprehensive assessment of the sector’s financial dynamics and its sensitivity to weather variations, thereby contributing to the literature through the construction of a dedicated renewable energy index for the French market. Using data from 54 weather stations, we apply Principal Component Analysis to reduce data dimensionality and extract the main weather factors. Furthermore, we employ both linear and non-linear econometric models, including the Threshold Autoregressive model, to forecast daily returns for the REFI and the CAC40 index. The results show that weather variables exert a statistically significant, though economically moderate, influence on market returns, with more pronounced effects observed for the REFI. The non-linear TAR model captures regime-dependent dynamics more effectively than linear benchmarks, suggesting that weather-return relationships intensify under specific market conditions. While the overall explanatory power remains limited, the findings enhance the understanding of how renewable energy-related assets respond to meteorological variability and offer useful insights for managing climate-related financial risks.
This study explores the nonlinear relationship between tariff barriers and current account balances across 13 Middle East, North Africa, and Turkey (MENAT) economies, using panel data from 2006 to 2023. Applying quadratic regressions and the Lind and Mehlum (2010) test, we confirm a U-shaped relationship between tariff barriers and the current account. This pattern emerges from an inverted U-shaped import-tariff dynamic and a U-shaped export-tariff dynamic. Specifically, we find that at lower tariff levels, increases in tariffs initially exert a detrimental effect on the current account balance, whereas at higher levels, the impact becomes beneficial. The estimated threshold of 11.6% delineates a pivotal point where increased tariffs transition from detrimental to beneficial for the current account balance. Accordingly, MENAT economies could strategically escalate tariffs up to this threshold to foster domestic industry growth and export capacity.
This study investigates the international spillover effects of inflation across twelve advanced and emerging economies, with a particular focus on the Asia-Oceania region. Employing a Time-Varying Parameter Vector Autoregression (TVP-VAR) model and the Connectedness Approach, we quantify the dynamic transmission of inflationary shocks from 2000 to 2025. Our analysis incorporates crude oil prices as an exogenous upstream variable and distinguishes between RCEP member countries and non-members.The results reveal that inflation spillovers intensify during periods of global shocks—such as the 2008 financial crisis, the COVID-19 pandemic, and geopolitical tensions—reaching Total Connectedness Index (TCI) levels as high as 90%. WTI crude oil consistently emerges as the strongest net transmitter, followed by China and Thailand. Japan functions as a moderate transmitter, with its role amplified during the post-earthquake and Abenomics periods. Since 2020, the United States has transitioned into a key transmitter, driven by aggressive fiscal and monetary policies and a strong dollar.Within the RCEP bloc, intra-regional inflation connectedness is substantial, with China, Thailand, and Japan serving as primary sources of price transmission. These findings underscore the need for monetary authorities to account for external inflationary pressures when designing domestic policy frameworks. The study contributes to the literature by offering a dynamic, regionally nuanced perspective on inflation spillovers and their implications for macroeconomic stability.
This study revisits Okun’s law for the European Union (EU) countries using sentiments as a potential threshold variable within a threshold regression (TR) framework. Using the FinBERT algorithm to measure sentiments, we take the communication tones of the most influential organizations as the source of asymmetric effects, namely those of the European Central Bank (ECB), the Federal Reserve (FED), the International Monetary Fund (IMF) and the United Nations (UN). The first two communication tones provide domestic and external monetary policy sentiments, whereas the last two provide sentiments for global financial stability and geopolitics, respectively. The threshold regression results suggest that asymmetric effects depend on the source of the sentiments, the temporal dimension of the analysis and is heterogeneous across countries. Moreover, the findings seem to reveal the rival-partner interdependence between the EU and the US, using the sentiments of the FED.
Corporate greenhouse gas emissions have emerged as a salient signal in financial markets, yet their implications for a core dimension of market quality, stock liquidity, remain insufficiently understood. Existing studies generally impose linear and symmetric relationships between environmental performance and financial outcomes, thereby overlooking potential threshold effects and regime-dependent investor responses. Drawing on a panel of 328 S&P 500 firms observed over the 2013-2022 period, this study examines whether total and scope-specific greenhouse gas emissions affect stock liquidity in asymmetric ways. Using a panel smooth transition regression approach, we allow liquidity responses to vary across emission regimes, offering a more subtle account of how environmental exposure is capitalized in trading conditions. The results reveal pronounced nonlinearities. Below critical thresholds, 3.566 for total emissions, 3.446 for Scope 1, and 3.156 for Scope 2, greenhouse gas emissions are associated with higher liquidity, consistent with market acceptance of emissions at lower levels. Once these thresholds are exceeded, however, there is a sharp decline in liquidity. By contrast, Scope 3 emissions exert a negative and significant linear effect across nearly all specifications, suggesting persistent investor difficulty in assessing and pricing supply-chain-related greenhouse gas risks. Nevertheless, in some specifications, the estimated effects of Scope 3 emissions remain unstable, reflecting fundamental measurement and attribution challenges inherent in value chain emissions data. These results jointly suggest that stock liquidity responds asymmetrically to environmental exposure in ways consistent with stakeholder tolerance, informational complexity, and risk management mechanisms, thus positioning environmental performance as a nonlinear determinant of market microstructure with tangible financial consequences.
We examine the effect of monetary policy shocks (MPS) on household inequality in India using Consumer Pyramid Household Survey data from 2014 to 2022. Using Jorda`'s local projections, we find that MPS affect income and consumption inequality asymmetrically, as contractionary MPS increase inequality while expansionary MPS have mixed effect. Large MPS have more pronounced effect on households' inequality than small MPS, highlighting the nonlinear effect of MPS on inequality. Further, contractionary MPS affect household income through earnings heterogeneity and income composition channels. The operating substitution and aggregate wealth channels of monetary policy affect consumption expenditure among households of different income strata. Since contractionary MPS aggravate inequality significantly, central banks in EMEs, as in India, focusing on price stability may also need to nuance the size and timing of the MPS. Concurrently, the distributional consequences of monetary policy should be monitored; however, rather than being directly targeted by central banks, they should be addressed by apposite and well-designed income-support fiscal policy measures.
This study investigates the role of sentiments expressed through various publications by international organizations, namely the International Monetary Fund (IMF), the World Trade Organization (WTO), the World Bank (WB) and the United Nations (UN) on electricity prices for 22 European Union (EU) countries, controlling for the main determinants used in the literature. Sentiments are measured using the finBERT algorithm. The analysis is carried out within a kink regression framework to account for possible asymmetric effects. Concentrating on the IMF, the findings suggest a negative and asymmetric effect of IMF sentiments on electricity prices in several EU countries during relatively more pessimistic periods.
This quantitative study examines the impact of the growing financialization of the Arabica coffee (Coffea arabica) futures market, as reflected in the widening gap between futures and spot prices, on smallholder producers' incomes and the generation of distributional asymmetries along the value chain. To this end, statistical techniques are employed, and two indicators adapted from existing approaches are operationalized: The Net Positioning Index (NPI), which captures net speculative bias, and the Positional Extremes Ratio (PER), which measures the persistence of speculative episodes. Both indicators are empirically validated using Threshold Regression and Threshold Autoregressive (TAR) models, confirming their ability to anticipate extreme speculative conditions and to capture their effects on the futures-spot price gap. The analysis covers the period 2014-2025 and relies on weekly position data from the Commodity Futures Trading Commission (CFTC), daily futures prices from the Intercontinental Exchange (ICE), and domestic spot prices. The results indicate that speculation has intensified the disconnect between international prices and producers’ realized revenues, with the gap reaching USD 1.21 per pound in 2025 and failing to transmit to the domestic market. Moreover, more than 70% of the weeks in 2024 exhibit extreme speculative episodes (PER >0.66), pointing to persistent speculative volatility. Overall, the findings provide empirical evidence of the regressive effects of financialization and offer analytical tools to inform mitigation policies and early-warning mechanisms in agricultural markets.
The renewed interest in commercial nuclear energy to potentially satisfy increasing electricity demand requires solving the policy and regulatory impasse in backend fuel cycle management. This paper fills a gap in the literature by providing a technical and quantitative analysis of material flows under various fuel cycle options and linking the latter to associated financial costs. Under current U.S. law the government is responsible for spent nuclear fuel management, which exacerbates industry specific environmental, informational, intergenerational, and economic asymmetries, this led to policy failure, and enormous costs borne by U.S. taxpayers. The paper is structured as follows. Section 1 provides an introduction. Section 2 reviews current literature. Section 3 provides some technical background. Section 4 presents a brief historical account of regulatory challenges, and an overview of legacy spent nuclear fuel. Section 5 presents the methodology, data used, and scenario selection. Section 6 develops scenarios 1-4. Section 7 discusses the results and section 8 concludes the paper and provides policy recommendations. We find that spent nuclear fuel management could cost taxpayers as much as $100 billion or produce revenues of around $11.3 billion. Policy recommendations to mitigate industry specific asymmetries, and lower costs to taxpayers are provided.
This study examines the non-linear effects of global economic policy uncertainty (EPU) on individual-level unemployment, using Barbados - a small, open economy with a fixed exchange rate - as our empirical example. To this end, we analyse the microdata used to compute Barbados's official unemployment rate between 2004 and 2022. Generally, we find that when global policy uncertainty increases, individuals face a higher likelihood of unemployment. However, our results also reveal that the effects of foreign EPU on unemployment are not uniform; instead, they exhibit significant heterogeneities and asymmetries. We find that younger individuals, men, those with post-secondary academic qualifications, and individuals employed in the construction, leisure and hospitality, and professional and business services sectors are particularly vulnerable to increases in uncertainties abroad. Our results suggest that unemployment reacts more strongly to uncertainty during economic downturns and periods of stagnation than during economic booms. Moreover, we observe that individual unemployment is slightly more affected by decreases in foreign EPU than by increases.
Economists and policymakers have deemed the green energy transition as one of the most effective tools for tackling climate change. Generally, strategic interactions across countries play a significant role in the effectiveness of environmental policies. This paper emphasizes the critical role of cross-border coordination. Our analysis builds upon a standard macroeconomic model of energy policy choices to incorporate emission externalities from neighboring countries and examine how these countries’ actions influence domestic decisions regarding the green transition. Our findings suggest that countries transition slowly because foreign emissions reduce the perceived benefits of domestic decarbonization. Thus, countries remain trapped in a Prisoner’s Dilemma, while international cooperation is a key mechanism for achieving the socially optimal outcome.
Energy security is essential for building resilient economies and sustaining economic growth, as it directly influences productivity, competitiveness, and overall economic performance. While existing research has explored the relationship between energy security and economic development, the asymmetric effects of energy security on economic performance remain underexamined. This paper seeks to address that gap. To test the asymmetric effects of energy security, we use various energy security proxies (domestic energy production relative to consumption, energy production per capita, renewable energy share, energy intensity, and energy consumption per capita) and employ a panel dataset of 117 countries from 2000 to 2022, and apply a panel quantile estimation method. The results reveal strong heterogeneity across income levels. Energy production relative to consumption and population, and energy consumption per capita, have stronger positive effects on GDP per capita in lower quantiles, highlighting the importance of energy availability and access in the early stages of development. By contrast, the renewable energy share has a negative effect in poorer economies but turns positive in richer economies, reflecting the high costs of renewable energy adoption for low-income countries and the benefits it generates in advanced economies. Energy intensity consistently has a negative impact, but the magnitude varies nonlinearly across quantiles, underscoring the role of energy efficiency. The results are robust to alternative sample compositions excluding microstates and to an aggregate measure of energy security constructed using principal component analysis. Overall, the findings suggest that energy policy should be tailored to countries’ development levels.
