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This paper examines the international effects of Chinese policy uncertainty shock. Using the factor-augmented vector autoregression (FAVAR) model which can accommodate several economic variables from multiple countries, we model Chinese policy uncertainty jointly with three latent factors extracted from industrial production index, import value and export value. The results reveal that the change of one standard deviation of Chinese economic policy uncertainty (EPU) has a negative interference effect on global trade markets and industrial production, and so does the fiscal policy uncertainty (FPU). However, the impact of Chinese trade policy and monetary policy on three latent factors is not statistically significant. A country-level analysis shows that due to the heterogeneity of the economic structure and trade structure of each economy, countries have different responses to the uncertainty of Chinese economic policy. In particular, the extent to which imports and exports of each economy are affected is asymmetric.

In search of a stable demand for money, almost all previous studies include two uncertainty measures captured by the volatility of the money supply and output. While in some countries, this yielded a stable demand for money, in some others, it did not. The latter was the case for Singapore. In this paper, we use a relatively more new and comprehensive measure of uncertainty known as policy uncertainty that is a news-based measure, and revisit the demand for money in Singapore. Our approach not only yields a stable demand for money in Singapore, but also reveals that the long-run effects of policy uncertainty on the demand for money are asymmetric. While increased uncertainty induces the public in Singapore to hold more money, decreased uncertainty does not affect.

The objective of this study is to evaluate the impacts of policy uncertainty and economic freedom on the stability of national banking systems worldwide. The research sample includes 165 countries and covers the period from 1997 to 2021. The study employs panel data estimation methods including the fixed effects model, random effects model, Driscoll–Kraay standard errors approach, and system GMM. The findings consistently show that policy uncertainties, including world policy uncertainty, trade policy uncertainty, and global economic policy uncertainty, negatively affect bank stability. Additionally, economic freedom policies can help mitigate the negative impact of policy uncertainty.

Does policy uncertainty affect productivity? Policy uncertainty creates delays on decision-making as firms await new information about prices, costs, and other market conditions before committing resources. Such delays can have real consequences on firms’ productivity and corporate decisions. We find that economic policy uncertainty has a negative impact on firm-level productivity. We further show that the negative impact is alleviated by firms’ high cash holdings or prior committed irreversible investments. These findings are robust to various specifications.

Since the 2015 Paris Agreement, SDG 13 for climate action has received substantial attention from governments to target carbon neutrality by 2030, highlighting the attractiveness of climate finance that comes across the fields from micro with corporate behavior to macro perspectives. In this chapter, I provide a systematic review of climate finance, policy uncertainty, and global financial stability through bibliometric analysis based on Web of Science Core Collection for all published peer-reviewed articles from 1900 onward. While uncertainty and financial stability have received long-term increasing attention from scholars since early 1990 to present day at a more constant rate, the scientific world has shown its high attention to climate finance during periods of crises since the 2008 global financial crisis (GFC), with an exceptional increase since COVID-19. The findings reflect the fact that we care (think) more about climate (stability) issues when crises emerge. The findings provide critical implications for market behavior and the world’s transition to SDGs where climate finance and global financial stability are open to many angles to be explored through the world’s times of uncertainty.

In July 2012, the Australian government introduced a Carbon Pricing Mechanism (CPM) to regulate national Greenhouse Gas (GHG) emissions. However, due to political controversies, there were concerns over the fate of this policy throughout its implementation. To determine the effect of carbon pricing policy on major electric utility companies, this chapter extracts an implied carbon price from the Australian electricity derivative market and models its volatility interaction with the utility index in Australian Stock Exchange (ASX).We find that Autoregressive Conditional Heteroscedasticity (ARCH) model can adequately simulate and forecast the dynamics of implied carbon price. As the cost of carbon emissions was fully transparent and passed onto the market, carbon pricing pushed up electricity prices, which subsequently enhanced expected stock returns of electric utility companies. While shocks from implied carbon price caused immediate response in the stock market, transfer of volatility from the latter to electricity derivative market was lagged. The persistent shift of volatility level further demonstrates the effect of carbon pricing and related policy uncertainty on the Australian electric utility sector. Findings from this chapter provide insight into market sentiment on carbon pricing policy and can contribute to financial risk management.