A5007174506- Market Dynamics and Volatility
- Energy, Environment, Economic Growth
- Monetary Policy and Economic Impact
- Energy, Environment, and Transportation Policies
- Housing Market and Economics
- Climate Change Policy and Economics
- Natural Resources and Economic Development
- FinTech, Crowdfunding, Digital Finance
- Financial Risk and Volatility Modeling
- Atmospheric and Environmental Gas Dynamics
- Banking stability, regulation, efficiency
- Financial Markets and Investment Strategies
- Global Energy and Sustainability Research
- Global Energy Security and Policy
- Firm Innovation and Growth
- Fiscal Policy and Economic Growth
- COVID-19 Pandemic Impacts
- Climate Change and Health Impacts
- Climate variability and models
- Complex Systems and Time Series Analysis
- Regional Economic and Spatial Analysis
- Petroleum Processing and Analysis
- Migration, Ethnicity, and Economy
- Educational Reforms and Innovations
- Wind and Air Flow Studies
CITIC Group (China)
2025
Anglia Ruskin University
2017-2025
Renmin University of China
2024
Shanghai University
2020
University of Huddersfield
2017-2019
University of Southampton
2017
University of Vaasa
2017
University of Helsinki
2017
Tsinghua University
2004-2011
This paper analyses the dynamic impact of geopolitical risks (GPRs) on real oil returns for period February 1974 to August 2017, using a time-varying parameter structural vector autoregressive (TVP-SVAR) model. Besides two variables concern, model also includes growth in world production, global economic activity (to capture oil-demand), and stock returns. We show that GPRs (based tally newspaper articles covering tensions), general, has significant negative returns, primarily due decline...
We analyse the impact of climate risks (temperature growth and its volatility) on coincident indicator 50 US states in a panel data set-up, over monthly period March, 1984 to December, 2019. Using impulse response functions (IRFs) from linear local projections (LPs) model, we show that negatively economic activity similar degree, irrespective whether such are due changes temperature or volatility. More importantly, using nonlinear LPs IRFs reveal adverse effect is contingent regimes...
Recent theoretical developments tend to suggest that rare disaster risks enhance the persistence of uncertainty. Given this, we analyse impact climate (temperature growth or its volatility), as proxies for such unusual events, on economic and policy-related uncertainty 50 US states in a panel data set-up, over monthly period 1984:03 2019:12. Using impulse response functions (IRFs) from regime-based local projections (LPs) model, show an shock itself is not only bigger magnitude when economy...
Abstract This paper explores the impact of bank digitalisation on corporate agency costs. The findings show that: (i) significantly reduces costs by improving banks' monitoring capabilities; (ii) financial regulation further lowers for firms engaging with more digitised banks; and (iii) effect between is weaker in state‐owned enterprises those short‐sighted management, but stronger greater financing constraints shorter listing durations. These results provide new evidence digitalisation's...
While there is a large body of literature on oil uncertainty-equity prices and/or returns nexus, an associated important question how market uncertainty affects stock bubbles remains unanswered. In this paper, we first use the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to detect both positive and negative in short-, medium- long-term markets G7 countries. detecting major crashes booms seven over monthly period February 1973 May 2020, also...
This paper examines the effects of climate change on income inequality in United States. Computing impulse response functions (IRFs) from local projections’ method, we empirically show that there is an immediate temporary positive rising temperatures within first year. We also observe differences temperature growth across different classifications, mainly states with high and low are more susceptible to changes than already growth. States exhibit similar low- high-temperature-growth...
Abstract This study explores the relationship and connectedness between oil returns financial stresses in six Gulf Cooperation Council (GCC) countries using daily data from September 21, 2006 to May 31, 2019. The Bayesian Graph‐based Structural Vector Autoregression (BGSVAR) model is utilised estimate analyse direction of causality. In addition, spillover approach examine risk transmission patterns GCC economies both time frequency domains. empirical analysis BGSVAR shows that have a...
This paper investigates both the linear and nonlinear effects of climate risk shocks on wealth inequality in UK using local projections (LPs) method, based high-frequency, i.e., monthly data. The results show that lead to an increase longer term. present some evidence heterogeneous responses variable between high- low-climate regimes. findings highlight disproportionate increased burden change households are already experiencing poverty, particularly high-climate areas. As such, measures...
Abstract We use the recently created monthly Interest Rate Uncertainty measure, to investigate monetary policy uncertainty across US, Germany, France, Italy, Spain, UK, Japan, Canada, and Sweden in both time frequency domains. find that largest spillover indices are from innovations country itself; however, there some instances where between countries large. These relationships change over we observe large variances pairwise spillovers during global financial crisis. most of volatility is...
This study investigates the impact of a metric extreme weather shocks on 32 state-level inflation rates United States (US) over quarterly period 1989:01 to 2017:04. In this regard, we first utilize dynamic factor model with stochastic volatility (DFM-SV) filter out national from local components overall, non-tradable and tradable rates, ensure that effect regional climate risks is not underestimated, given derived sizeable common component. Second, using impulse responses linear nonlinear...
Western literature shows evidence of a positive relationship between socio-spatial features neighbourhoods and social interaction. However, there is little research exploring this in the Chinese context, particularly locals migrants peri-urban China where significant housing being created. This paper studies supporting interaction across different neighbourhood types areas Guangzhou. In research, data were collected using door-to-door questionnaires site surveys 9 The nature strength...
This paper uses a time-varying parameter-panel vector autoregressive (TVP-PVAR) model to analyze the role played by domestic and US news-based measures of uncertainty in forecasting growth industrial production 12 Organisation for Economic Co-operation Development (OECD) countries. Based on monthly out-of-sample period 2009:06 2017:05, given an in-sample 2003:03 2009:05, there are only 46% cases where can improve forecast output relative baseline monetary TVP-PVAR model, which includes...
This paper seeks to investigate the motivations of countries that participate in One Belt and Road (B&R) Initiative, a China-led economic development program with intention enhancing regional cooperation. We examine income convergence hypothesis for B&R both linear nonlinear unit root tests detect presence integration over periods 1960–2016 1979–2016. For are found show China our testing, we argue they tend have strong existing relationship China. By contrast, relatively weak...
In this study, we analyse the impact of oil price uncertainty (as measured by an observable measure volatility, i.e. realised volatility) on United States state-level real consumption accounting for dependency. We account both long- and short-run dynamics function using panel Pooled Mean Group estimator. The analysis makes use a novel dataset including housing stock market wealth at state level covering quarterly period 1975:Q1 to 2012:Q2, supplemented with annual up 2018. simultaneously...