Purpose This paper aims to explore the role of two transmission channels between “green” transition and (overall and core) inflation, the so-called “greenflation” in the USA. The first channel is related to the “green” macroeconomic characteristics, and the second channel is associated with the “green” banking/financial characteristics of the US economy. Design/methodology/approach The empirical analysis spans the period 1990–2023, while it uses two-stage least square regressions and causality tests. The analysis is conducted across the full sample and sub-periods to assess robustness and structural shifts. Findings The findings through regression estimates and causality tests, clearly document that both channels (fiscal spending on renewables and “green” credit) impact inflation, validating the effect of “green” transition on inflation, with the “green” credit channel having the strongest effect, followed by the mechanism of “green” fiscal spending. Originality/value To the best of the authors’ knowledge, this study is the first to determine the primary channels through which the “green” transition impacts inflation. It offers first-time evidence on the role of fiscal spending on “green” transition and “green” credit on inflation.
Purpose This study aims to investigate the impact of geopolitical risk on selected energy and precious metal commodities, namely WTI crude oil, Brent crude oil, natural gas, gold and silver. Design/methodology/approach The study uses a Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity Mixed Data Sampling (DCC GARCH MIDAS) model to examine the relationship between geopolitical tensions and commodity price volatility. This framework enables the integration of lower-frequency geopolitical risk measures with higher-frequency commodity price data, providing a nuanced view of their dynamic linkages. Findings The results confirm that energy commodities, particularly the two benchmark crude oils (WTI and Brent), are highly sensitive to geopolitical uncertainty. The strongest positive correlation between geopolitical risk and oil prices is observed during the Russia–Ukraine invasion. In contrast, gold and silver exhibit relatively low correlations with geopolitical risk and their price responses appear to be more event-specific. Originality/value This study contributes to the literature on geopolitical risk by jointly examining its effects on both energy commodities and precious metals. The findings show that gold’s hedging capacity is not consistently effective, as its role as a hedge appears to depend on the nature of the geopolitical event. Overall, the results provide useful insights for risk management in periods of heightened geopolitical uncertainty.
Purpose This study aims to explore the role of green finance in achieving a cleaner environment. More specifically, it examines the short- and long-run impacts of green finance on environmental degradation. Design/methodology/approach This study uses balanced panel data for a selected set of seven BRICS + nations, covering 2000–2023. It uses a panel Autoregressive Distributed Lag (ARDL) or a pooled mean group (PMG) model to assess the impact of green finance on ecological footprint (EFP). The panel ARDL model provides long- and short-run coefficients and an error-correction term, clearly showing the dynamics of the relationship between green finance and environmental sustainability. Findings The findings reveal that green finance significantly and negatively affects the EFP in the long run, but has no such impact in the short run. As green finance supports environmentally friendly investments in an economy, it can reduce harmful environmental emissions over time, but because these projects require longer gestation periods, the beneficial impact on the environment does not appear in the short run. Research limitations/implications Green finance plays a crucial role in the green transformation of the financial system by promoting environmentally friendly investments. Green finance instruments such as green bonds, sustainability-linked loans and carbon credit financing are valuable for financing environmentally friendly projects and reducing EFPs. Originality/value This study adds to existing literature on green finance by exploring its impact on EFP. Research on this field is relatively scarce in the existing literature for BRICS+.
Purpose This paper aims to examine whether the forces linking financial markets to real economic activity operate differently across business cycle phases, using quarterly US data from 1990 to 2024, spanning four recession episodes. Specifically, the author asks whether the mechanism that normally keeps equity markets anchored to corporate earnings and real output remains stable between expansions and recessions and what the accumulated output cost is when that mechanism breaks down. Design/methodology/approach The author first estimates a vector error correction model among real gross domestic product (GDP), the S&P 500 Total Return Index and Earnings Per Share, using cointegration tests to identify the long-run equilibrium structure and controlling for monetary policy, consumer confidence, market uncertainty and real GDP expectations. The author then extends this to a Bayesian Markov-Switching vector error correction model that holds the cointegrating vectors constant while allowing adjustment dynamics and shock covariance structures to vary across regimes, with regime identification anchored to NBER recession dates. Findings The author identifies two stable long-run equilibria anchored by earnings per share. This study finds that the stock market index self-corrects toward its earnings equilibrium in normal expansions, while in recessions, the adjustment coefficient linking the stock market index to earnings reverses sign, with the index moving further from earnings fundamentals; as the Granger causality tests detect predictive content from stock returns and earnings growth to GDP growth but not in the reverse direction, no offsetting predictive force is found within the estimated system. The accumulated output cost amounts to 1.78 percentage points of cumulative GDP growth deficit by quarter 20 following a recession onset. Originality/value The author provides direct evidence that the corrective mechanism linking the stock market index to its long-run earnings equilibrium is regime-dependent, reversing during recessions in a way that has not previously been documented within a regime-switching cointegration framework.
Purpose This study aims to detect speculative price bubbles in major cryptocurrencies and NFT indices and measure how sentiment from the cryptocurrency market, NFT market and broader equity market uncertainty transmits across these digital assets.Design/methodology/approach Using daily data from May 6, 2021, to March 1, 2024, this study examines the dynamic price changes in Bitcoin (BTC), Ethereum (ETH), the NFT Blue-Chip Index (BCI) and the NFT Potential Index (PNI). Bubble episodes are identified via the Backward Supremum Augmented Dickey-Fuller (BSADF) procedure. To model dynamic spillovers between returns and sentiment, a vector autoregression (VAR) is estimated incorporating equity-market volatility (VIX), the crypto Fear and Greed Index and NFT/market sentiment indicators.Findings Findings reveal various speculative bubble episodes in BTC, ETH and the NFT BCI, indicating recurrent boom-burst dynamics in core crypto and mature NFT segments. VAR estimates show significant sentiment and risk transmission across markets. BCI generates a significant positive spillover to BTC and ETH returns, suggesting that mature NFT activity can act like a multiplier on the normal boom-bust pattern of BTC/ETH by adding extra momentum into crypto returns. Market sentiment is significantly negatively associated with subsequent ETH returns, consistent with short-run corrections after optimism. Finally, VIX and NFT sentiment are significantly linked to NFT index movements, and the NFT Potential Index (PNI) is particularly sensitive to broader risk conditions and NFT-specific sentiment.Practical implications Findings provide useful information and strategy recommendations for investors, portfolio managers and financial regulators in digital assets. Investors should monitor NFT sentiment and market volatility as indicators of price dynamics in cryptocurrency markets.Originality/value Through an in-depth analysis of the relationship between the sentiment indicators of the stock market, the NFT market and the cryptocurrency market, this paper supports the transmission effect mechanism of market sentiment among different markets.
