This study examines global inflation co-movement by employing a dynamic factor model with time-varying parameters and stochastic volatility to extract global, group, and country-specific factors across 86 developed and developing economies from 1971 to 2023. The results reveal that (i) the global factor has gradually receded as the primary source of inflation variation, giving way to more group- or country-specific dynamics-though brief episodes of global synchronization reemerge during major crises; (ii) the group factor dominates inflation variation in developed countries; and (iii) the country-specific factor remains the main driver of inflation in developing countries.

The Prebisch-Singer (1950, PS) hypothesis posits a long-term decline in the relative prices of primary commodities (natural resources) compared to manufactured goods. This hypothesis carries important implications for resource management, economic growth, and the terms of trade in developing countries. It raises two critical questions that are inherently interlinked: (1) Do relative commodity prices exhibit a negative trend? and (2) Are these prices non-stationary? When addressing these questions, prior analyses have often overlooked the potential influence of cross-correlations among relative commodity prices. In this study, we jointly address these questions while explicitly accounting for cross-correlations. To achieve this, we first employ a dynamic factor model, which effectively captures the shared variations across commodity prices. Additionally, we incorporate the Fourier function to model smooth structural breaks, allowing for the identification of gradual changes in the underlying trend. The combined use of these methods yields significant insights. Our findings provide robust evidence supporting the PS hypothesis over the period 1900-2020, highlighting the persistent and systematic decline in the relative prices of primary commodities.

This study examines the persistence of shocks to stock prices in emerging markets, with accounting for non-normal distributions, structural changes and asymmetry by means of the recent developments in the quantile autoregression models. The results, from the data covering the January 1988-January 2025 period for the stock price index of 24 emerging markets, show the importance of simultaneously accounting for these data properties in analysing the effects of shocks to stock prices. We find that the shocks tend to be temporary, demonstrating a mean-reversion in stock prices of emerging markets, which provides implications for trading strategies, portfolio investment and risk management.

Previous research demonstrates that housing prices frequently move in tandem across regions, underscoring the interconnectedness and correlation present within housing markets. Building on this foundation, our study advances the analysis by examining quantile co-movements and the synchronization between local and national housing markets. Using the quantile factor model across the full distribution of housing prices, we identify distinct factor structures at the lower and upper tails that contrast with those observed in the middle of the distribution. This analytic framework enables the detection of previously hidden factors influencing housing markets. With this approach, we illuminate how housing price dynamics interact across market segments, price levels, and geographic areas. Our findings reveal that co-movements can vary substantially across low, stable, and high housing price regimes, thus providing more comprehensive and nuanced economic insights into the complex nature of housing price fluctuations.

The growing empirical literature documents evidence on persistence of shocks to inflation; however, little is known about the nature of inflation shocks with asymmetric persistence and cross-correlations. By introducing panel quantile unit root approach with common shocks for a sample of 75 countries from January-1980 to December-2022, this study provides new insights on the persistence of inflation shocks. The panel quantile unit root analysis sheds light on that (i) inflation appears to exhibit significant cross-correlations across countries at all quantiles, and persistence of inflation shocks shifts notably between low and high quantiles, reflecting asymmetric persistence in inflation dynamics, (ii) inflation rates tend to be mean reverting during low to moderate inflation periods, but more persistent in high inflation period, (iii) inflation becomes persistent at higher thresholds in countries with a history of inflationary episodes. These findings reveal the importance of considering asymmetric persistence and cross-correlations for analyzing inflation shocks.

The purpose of this study is to examine whether inflation co-movement has a time-varying behavior. We estimate a dynamic factor model with time-varying variances and obtain variance decomposition for G7 countries from 1970 to 2023. The results reveal that (i) inflation co-movement tends to change with global shocks, with a more synchronized pattern during global financial crisis and COVID-19; and (ii) it tends to cluster across countries after COVID-19, with an increase in US, Canada, and Japan and a decrease in European countries (France, Germany, Italy, and UK). These findings hence provide new insights on time-varying inflation co-movement.

The growing empirical literature documents evidence on increasing global inflation co-movement across countries over time; however, little is known about the quantile co-movement structure of inflation. By introducing quantile factor model for a global sample of 151 countries from 1970 to 2023, this study provides new insights with respect to inflation co-movement. The quantile factor analysis sheds light on that (i) global inflation has a quantile-dependent factor structure, with different behavior in low, mild/stable, and high inflation periods; (ii) inflation shows an asymmetric co-movement pattern, with a decreasing degree in low and high inflation periods in comparison with stable inflation period; (iii) while interest rate and economic activity are the underlying observables for the latent quantile factors in low and stable inflation periods, commodity prices also become an underlying observable in high inflation period; and finally (iv) using quantile factors is nontrivial in improving density forecast of inflation in both developed and emerging markets.

Are the economic freedom levels of all countries converging now that the Cold War is over? If not, are they converging into a subset of economic freedom groups or ‘clubs’ based upon underlying legal origins and country characteristics? This study investigates these questions using recent methodological developments in panel data convergence analysis. Our tests indicate non-convergence of economic freedom across all countries. However, club convergence tests reveal three distinct convergence clubs. Our subsequent results demonstrate that countries belonging to the higher economic freedom convergence clubs are less likely to have French legal origin and lower reliance on natural resource rents, and more likely to have long tenured and democratic governments, easier exitability, more net migration, faster economic growth, more control of corruption, as well as more elderly and dense populations.

Investment in renewable energy production has been subject to swings in the U.S. policy stance on climate change creating uncertainty. Determining how and to what extent the renewable energy sector responds to climate policy uncertainty is relevant to understanding the energy transition from fossil fuels to renewables. This study examines the relationship between the growth in renewable energy production and its sub-components and climate policy uncertainty while accounting for oil price uncertainty and the growth in oil prices, industrial production, and carbon emissions, respectively. Utilizing generalized impulse response analysis within a vector autoregressive model framework, we find that total renewable energy production responds negatively to shocks to climate policy uncertainty but exhibits only a small positive response to oil price uncertainty. Further examination of renewable energy production by its sub-components (i.e., hydropower, biomass, geothermal, wind, and solar) shows that the time path responses to uncertainty shocks differ by sub-component. The findings suggest that policies to facilitate an energy transition by treating renewables similarly may not have the desired effects and thus should be tailored to individual sub-components to achieve targeted goals for renewable energy production.

This study investigates long-run price and volatility integration between U.S. regional housing markets and both energy and non-energy commodities. The analysis applies Fourier-augmented Toda-Yamamoto models to examine price transmission and Fourier-augmented causality-in-variance tests to assess volatility spillovers, conditioning commodity indexes on region-specific heating degree days to preserve long-run information while capturing smooth structural changes. After controlling for macroeconomic factors and weather-driven demand, the results show that oil remains integrated with housing prices and that oil-related volatility exhibits widespread, often bidirectional spillovers with housing markets-highlighting the central role of oil as both an input cost and a macro-financial barometer. In contrast, natural gas and coal display little evidence of persistent integration once weather demand and gradual shifts are accounted for, and their volatility spillovers are limited and region-specific. The non-energy results provide a comparative benchmark: industrial metals generate long-run integration in construction-intensive regions, agriculture primarily contributes through volatility associated with household-budget and income channels, and precious metals transmit state-contingent volatility consistent with safe-haven and portfolio behavior. Overall, persistent integration is strongest and most durable for oil, whereas other energy and non-energy commodities display more selective and region-specific linkages. These findings underscore the importance of regional policy on heating-fuel choices and the management of petroleum-linked costs, while offering guidance for investors seeking to hedge oil exposure and construction-input risk in rapidly growing housing markets.

This study examines the evolving integration - or 'financialization' - of commodity and equity markets, focusing on how diversified U.S. equity mutual funds interact with both energy and non-energy commodities. We employ a Fourier Volatility Transmission Analysis to detect volatility spillovers between 1404 diversified equity funds and commodity markets. This approach is particularly adept at capturing gradual structural shifts that traditional models often miss. In the subsequent phase, we investigate whether individual fund characteristics, including ESG dimensions, influence the probability and strength of these transmissions. Our empirical findings reveal significant volatility spillovers between fund returns and commodity prices, with energy commodities exhibiting a higher degree of financialization compared to non-energy commodities. Notably, ESG criteria emerge as important determinants in shaping these interactions, though their impact on fund flows is relatively muted. These findings suggest that managers, who predominantly control returns, may be more susceptible to ESG components than investors (via flows). This possible disconnect can have significant market and policy implications. Requiring standardized and transparent ESG metrics can aid both managers and investors in understanding the impacts of ESG dimensions on volatility integrations and aligning their strategies.

This letter examines the persistence of unemployment in the United Kingdom (UK) using over a quarter of a millennium of data, spanning from 1760 to 2023. The results from the quantile unit root approach—accounting for non-normal distributions, structural changes, and non-linearity—reveal asymmetric unemployment dynamics. Shocks to unemployment appear transitory in low-unemployment regimes but are persistent in high-unemployment regimes. The findings highlight the importance of accounting for asymmetries in labor market adjustments.

Since the seminal paper of Nelson and Plosser (J Monet Econ 10(2):139–162, 1982), analyzing the nature of shocks to macroeconomic and financial data has attracted great attention and it continues to be up-to-date, especially, in conjunction with the advances in unit root literature. This paper examines the persistence in macroeconomic and financial variables for Turkey by means of the recent developments in the quantile autoregression models to account for non-normal distributions, structural changes, and asymmetric dynamics. The results show that while the conventional unit root approaches fail to reject the null hypothesis of unit root for most the of 30 macroeconomic and financial time series, the nonlinear quantile unit root test with smooth structural changes supports evidence on a stable long-run equilibrium for 23 variables. It further reveals asymmetric persistence in most of the Turkey’s macroeconomic and financial data, implying that the effect of an economic shock in inflationary state is different than that in recessionary state.

This study investigates the persistence in Turkish interest and inflation rates since the implementation of inflation-targeting monetary policy, covering the period from January 2006 to July 2022. We focus on accounting for asymmetric persistence by benefiting from recent developments in quantile unit root analysis. The findings indicate that while the conventional unit root tests support the persistence of shocks to interest rates and inflation, the quantile unit root test demonstrates an asymmetric behaviour of the persistence, implying a time-varying structure with mean reversion (persistency) of the shocks in low (high) inflation periods. Furthermore, the half-lives increase with the positive shocks, indicating a longer speed of adjustment in the high inflation regime. These findings provide new insights into the relationship between interest rates and inflation and have sound policy implications.

Oil and Natural Gas markets are integrated with equity markets over time. While the integration characteristics vary between type, direction, and magnitude, this persistent relationship yields questions about oil's and natural gas's place in diversified portfolios. Since general equity markets are observed to integrate with these specific energy commodities, similar relationships are expected with diversified equity mutual funds. In recent years, the Environmental, Social, and Governance (ESG) characteristics of firms have attracted attention from the market participants. Firms' ability to incorporate policies and procedures that are mindful of ESG dimensions is suspected to influence investor and manager decisions. In this study, we first test different integration levels between diversified equity mutual funds and oil and natural gas markets. After identifying these relationships, we test whether ESG components of funds impact the probability of integration. Our results provide evidence of strong integration. More importantly, we show that ESG's impact on integration differs between diversified equity fund flows and returns.

This study examines the stochastic convergence of renewable energy intensity (REI) across US states. We test for the stationarity of relative REI (stochastic convergence) using a recently developed quantile panel unit root test that accommodates both cross-sectional dependence and asymmetric behaviour. Our overall finding is that most states exhibit convergence, which implies that economic growth is sustainable with a higher share of renewable energy in the energy mix. This result provides support for those advocating that state governments should increase investment in renewable energy in advancing the clean energy transition. However, over half of the states display asymmetric stochastic convergence, which implies that how effective policies will be in promoting renewable energy efficiency will depend on the size and type of shocks impacting REI. Our results imply that in states that encounter relatively large positive shocks to REI, it may be necessary to invest more in the diffusion of renewable energy technologies and set long-term targets. Asymmetric convergence behavior also makes it difficult to coordinate policy responses across states, providing support for a decentralized approach in which each state invests in renewable energy technologies specific to their unique economic circumstances, rather than adopting a mandated overall national policy approach.

We test the efficient market hypothesis (EMH) in emerging markets by simultaneously considering gradual shifts and common factors. Findings indicate that (i) while the test with sharp breaks does not support EMH, the tests with gradual/smooth shifts and common factors support EMH in emerging markets; (ii) considering structural breaks as a gradual process within a common factor framework is important for emerging financial markets; and finally (iii) increasing time span sheds light more on EMH.

The Prebisch-Singer hypothesis implies divergence in the terms of trade between developing and developed countries but does not eliminate the possibility of convergence if productivity in developing countries’ exports sufficiently improves. This study constructs a new and unique export sophistication dataset for the productivity of high-technology export products to examine convergence behavior of developed and emerging market countries. Relative and weak σ-convergence tests reveal overall productivity divergence in international trade. However, there are convergence clubs whereby income, R&D expenditures, foreign direct investment, and educational expenditures yield similar effects on the convergence club formation in both developed and emerging market countries.