Chinese Economic Policy Uncertainty Research Articles

Climate risks and the realized higher-order moments of financial markets: Evidence from China

The return distribution of energy assets deviates from the normal distribution, making volatility a partial measure of risk, and climate risk tend to affect the skewness preferences of environmentally conscious investors. However, limited evidence exists on the impact of climate risk on higher-order moments of asset returns, especially in China. Using data from December 2013 to June 2022, we study the time-varying Granger causal flow from two Chinese climate uncertainty indices (Chinese climate policy uncertainty (CPU) and Chinese climate uncertainty (CU)) to the realized high-order moments (volatility, skewness, and kurtosis) of various Chinese assets covering green energy, carbon emission allowances, and brown energy indices. The main results show evidence of time-variation in the causal flows from climate risks, without ignoring the heterogeneity between the two climate risk measures and across the three assets under study. Granger causality spans various time periods, and is generally more significant for the realized volatility. These results are robust to the specification of the time-varying causality analysis. They also remain significant when accounting for the impact of Chinese economic policy uncertainty, which further supports their robustness. These findings highlight the ability of climate risk to affect higher-order moments of asset returns through the channels of strong deviation of returns from the normal distribution, the preference of investors for skewness, and the frequent occurrence of crisis periods.

The Co-volatility of Uncertainty Shock on Chinese Exchange Rate: Based on Time-frequency Domain and Time-varying Method

In recent years, with the global epidemic, the Russia-Ukraine conflict, the great power game, and so on events, the international political and economic environment has become more and more unstable, the USDCNY exchange rate fluctuates significantly, and the external uncertainty risk shocks negatively hit the foreign exchange market. Based on this, this article expands global uncertainty risk shocks into four dimensions: global geopolitical risk, U.S. economic policy uncertainty, Chinese economic policy uncertainty, and VIX index, in addition to adding international WTI crude oil and gold price as additional variables, which are significantly correlated with both, to study the linkage among uncertainty shocks, commodity volatility and USDCNY exchange rate from the time-frequency domain. Furthermore, we analyze the time-varying spillover effects among variables at different frequency scales by decomposing the data into multiple scales using the Maximum Overlap Discrete Wavelet Transform (MODWT). Findings reveal that uncertainty factors and commodity prices exert distinct influence mechanisms on the USDCNY exchange rate under different cycles of frequency fluctuations. At various time-frequency domain volatility scales, VIX and WTI generate significant risk spillovers over the USDCNY exchange rate. Moreover, when global major events occur, time-varying spillover effects of variables are also heterogeneous. The research findings presented in this paper can provide valuable insights for policymakers and investors regarding the impact of international uncertainty shocks on the Chinese exchange rate across various short, medium, and long frequencies. This understanding can aid in managing uncertainty risks in decision-making processes, ultimately facilitating the efficient functioning of the foreign exchange market.

Connectedness and risk spillover in China's commodity futures sectors

AbstractThis study employs minimum spanning tree and generalized forecast error variance decomposition methods to investigate the connectedness and risk spillovers across China's commodity sectors from January 2016 to December 2021. The results show that total connectedness within the commodity system is time varying. Chemical is the main risk driver, while other sectors occasionally dominate the system. These two methods achieve consistent results in identifying the systemically important sector and dynamic connectedness. In addition, we find that Chinese economic policy uncertainty and the investor sentiment index have significant impacts on total connectedness. Our findings have implications for preventing systemic risk for policymakers and managing commodity portfolio risk for investors.

Asian stock market volatility and economic policy uncertainty: The role of world and regional leaders

This paper investigates the relative influence of the United States, China, Japan and the European Union on Asian stock markets from the perspective of economic policy uncertainty (EPU). The empirical setting assumes that stock markets evolve through high- and low-volatility regimes with a probability driven by EPU in these leader countries. The main result of the paper indicates that Chinese EPU surpasses Japanese and US EPU as the main driver of Asian stock market volatility, except in the South Korean and Hong Kong stock markets. Moreover, Chinese policy-specific uncertainty indices, such as monetary, fiscal, trade and exchange rate policies play a significant role but in the most developed financial markets only. These result provides further evidence that China’s economic and financial ties with its near neighbors are deepening, which has important implications for the regional institutions tasked with promoting and monitoring regional financial stability.

Connectedness and economic policy uncertainty spillovers to the ASEAN stock markets

Uncertainty regarding Chinese and American economic policies impacts major investable asset classes in politically contestable geographic regions such as Southeast Asia. Our objective is to examine the dependence structure of Chinese and American Economic Policy Uncertainty (EPU) and returns on six Association of Southeast Asian Nations (ASEAN) stock indices and to assess the impact of a significant statecraft consideration, the One Belt One Road (OBOR) Initiative, and an exogenous shock, the COVID-19 crisis, on the connectedness between EPU and ASEAN stock returns. We do so by employing novel connectedness and copula approaches. We find that American and Chinese EPU influence ASEAN equity indices differently across countries, with the connectedness of US EPU and ASEAN stock markets exceeding that of Chinese EPU post-2002. Further, we find that the introduction of the OBOR Initiative by China in 2013 coincided with a slight change in the dependence structure for several individual ASEAN stock indices, and show that the impact of the COVID-19 pandemic on the relationship between American and Chinese EPU and individual ASEAN stock index returns was not homogenous across countries. In doing so, we shed new light on the vulnerability of ASEAN member capital markets to statecraft considerations and exogenous shocks, as well as to economic policy decision-making in China and the United States.

Volatility forecasting of Chinese energy market: Which uncertainty have better performance?

This paper examines the effects of seven uncertainty indices on Chinese energy price volatility and analyses the influencing factors using the extended GARCH-MIDAS model. Our in-sample analysis shows that energy market volatility is negatively impacted by global and Chinese economic policy uncertainty (GEPU, CNEPU), the geopolitical risk act index (GPRA), and the climate policy uncertainty index (CPU). Out-of-sample forecasting results demonstrate that the CPU is a major cause of energy volatility in China, and our extended model exhibits higher forecast accuracy. Additionally, we discover that the CPU has a greater capacity for energy volatility during periods of low volatility, while high energy volatility is often associated with GPR. Finally, the outbreak of the Russia-Ukraine conflict resulted in a decline in the predictive capacity of the CPU while causing a boost in the EPU's predictive power.

Comparing the impact of Chinese and U.S. economic policy uncertainty on the volatility of major global stock markets

This study compares the impact of Chinese and U.S. economic policy uncertainty (EPU) (proxied by the EPU index) on the volatility of 11 major stock markets. Unlike previous research that only utilizes monthly EPU for such a comparison, this study uses both daily and monthly data to examine the impact within a month as well as over months. In order to provide a detailed analysis, EPU shocks are investigated from a two-sided viewpoint: one considering the effects of EPU indices as exogenous shocks, and the other examining the spillovers from EPU indices as endogenous variables. Meanwhile, the role of global turmoil, such as the 2007–2008 global financial crisis (GFC) and the COVID-19 pandemic, in influencing the impact of Chinese (or U.S.) EPU is highlighted. The results show that the impact of U.S. EPU is reinforced at both daily and monthly frequencies during the GFC, with a greater effect on the European stock markets. After the GFC, the rising influence of Chinese EPU is observed at a monthly frequency in several markets in Asia and elsewhere. Overall, the dynamic spillovers from the EPU indices to stock volatility suggest the dominant role of U.S. EPU in most markets at a daily frequency, while the extent of the spillovers is driven by turbulent events, including the GFC and the COVID-19 pandemic.

Global and domestic economic policy uncertainties and tourism stock market: Evidence from China

This study investigates the impacts of global economic policy uncertainty (GEPU) and domestic (Chinese) economic policy uncertainty (CEPU) on the long-run volatility of the tourism stock market in China based on an improved GARCH–MIDAS–X model. Empirical results reveal that both CEPU and GEPU have significant negative effects on the long-run volatility of China’s tourism stock market. It is further identified that the impact of GEPU on tourism companies’ performance is short-lived. The findings suggest that tourism-related practitioners should monitor both CEPU and GEPU when conducting risk assessments related to tourism investment and policymaking.

Climate risk and Chinese stock volatility forecasting: Evidence from ESG index

This study employs a generalised autoregressive conditional heteroscedasticity mixed data sampling model (GARCH-MIDAS) to explore the forecasting performance of Chinese climate uncertainty (CU), Chinese climate policy uncertainty (CEU), Chinese economic policy uncertainty (CEPU), and US climate policy uncertainty (UCU) in both CSI 300 ESG and SSEC index volatility forecasting. The empirical results indicate that CU and CEU can significantly drive CSI 300 ESG volatility and outperform CEU and UCU. This may be caused by investors paying more attention to climate risk with the advent of the ESG score.

Asymmetric impact of economic policy uncertainty on cryptocurrency market: Evidence from NARDL approach

The study examines the relationship between cryptocurrency market and economic policy uncertainty (EPU) by concentrating on the top five cryptocurrencies assessed by market capitalization. We investigate long and short-run effects of global EPU on the returns of Bitcoin, Ethereum, Tether, Binance coin and Ripple, along with ascertaining asymmetries, through the NARDL (Non-Linear Autoregressive Distributed Lag) model, for the period ranging from September 2017 to August 2022. In the long run, except for Tether, all other cryptocurrencies are negatively affected by EPU, challenging the safe hedge properties of cryptocurrencies. However, Bitcoin, Ethereum, Binance coin and Ripple display positive relations with growing EPU in short run, reflecting their safe haven attributes over a shorter horizon. Additionally, these cryptocurrencies exhibit asymmetries in the short run. Further, we analyse the effect of US, Chinese and Indian EPU on bitcoin returns to understand the effect of EPU shocks of advanced and emerging economies. US EPU has long-run negative effects on bitcoin market, whereas Indian and Chinese EPU have no significant impact in long term. Moreover, our analysis also establishes the detrimental impact of the Indian government's crypto tax policy on bitcoin. The study has relevance for current and potential investors of the cryptocurrency market apart from the policymakers and regulatory bodies.

Twitter-based Chinese economic policy uncertainty

Given the strict censorship in China, would tweets about Chinese economic policy uncertainty by global Twitter users contain valuable information above and beyond existing indices? We construct novel daily and monthly frequency "censorship-free" indices of Twitter-based Chinese economic policy uncertainty from March 2010 to April 2022, based on a total of 76,765 tweets that contain words about Chinese economic policy uncertainty. Our uncertainty index reasonably spikes during major economic policy events. Shocks to our index are significantly associated with future Chinese stock market returns as well as investment, consumption, unemployment, and production while existing Chinese economic policy uncertainty indices are not significantly related to economic outputs.

Time-varying higher moments, economic policy uncertainty and renminbi exchange rate volatility

We investigate the predictive value of time-varying higher moments and economic policy uncertainty (EPU) for renminbi exchange rate volatility. To do so we develop a generalized autoregressive conditional heteroscedasticity (GARCH) mixed data sampling (MIDAS) model with skewness and kurtosis (the GARCH-MIDAS-SK model), which accommodates time-varying non-Gaussianities (higher moments) of the renminbi exchange rate return distribution and allows us to link volatility to EPU. An empirical analysis based on daily USD/CNY exchange rate returns and monthly global EPU index data shows that the GARCH-MIDAS-SK-EPU model, which incorporates time-varying higher moments and global EPU, can yield more accurate out-of-sample renminbi exchange rate volatility forecasts than the various competing models (ie, the GARCH, GARCH-MIDAS, GARCH-MIDAS-EPU and GARCH-MIDAS-SK models). The superior predictive power of the GARCHMIDAS- SK-EPU model is robust to an alternative version of the global EPU index, alternative out-of-sample forecasting windows and local EPU indexes (Chinese EPU and US EPU). Our empirical findings highlight the value of incorporating timevarying higher moments and EPU into forecasts of renminbi exchange rate volatility.

경제 불확실성과 한국 기업의 투자

This study investigates the effect of economic uncertainty on firm investment. 67,128 observations from 2006 to 2017 of 5,594 Korean firms from the Business Activity Survey and economic policy uncertainty (EPU) indices of Korea, the United States, and China are used as data. The long-term cointegration relationship between firm sales and capital stock is confirmed, and the hypothesis that economic uncertainty affects firm investment along with demand is verified through an error correction model. In particular, Korean firms with subsidiaries in the US and China are analyzed separately to investigate the effect of the US and Chinese EPU. According to the analysis, Korean firms show a short-term reduced response to irreversible investment, so that the coefficient of influence of the square term of the change in sales on the change in firm investment shows a positive coefficient (a convex type of firm investment response). In addition, economic uncertainty affects firm investment through interaction with sales change (the cautionary effect). In particular, the cautionary effect was more significant and clear when China’s economic uncertainty was taken as an independent variable.

The hedging role of US and Chinese stock markets against economic and trade policy uncertainty: lessons from recent turbulences

PurposeThis study analyses the impact of economic and trade policy uncertainty on US and Chinese stock markets. Also, this study examines the hedge and safe-haven properties of US and China stocks against both US and Chinese economic and trade policy uncertainty.Design/methodology/approachTo achieve the desired goals, the authors employ Dynamic Conditional Correlation through Glosten et al. (1993) model based on the Generalized Autoregressive Conditional Heteroscedasticity (DCC-GJR-GARCH (1, 1)) and Quantile cross-spectral (QS) models. The study uses monthly observations spanning from March 2010 to June 2022.FindingsThis study evidence that the economic and trade policy uncertainty between USA and China is extremely sensitive and has high volatility clustering effects on DJChina88 and DJUS, respectively. Conversely, against the Chinese economic and trade policy uncertainty, the US stock market indexes show both hedging properties across the period and safe-haven during COVID-19 and Russia–Ukraine crises. In contrast, among the Chinese stock markets, only DJShenzhen and DJShanghai stock indices might provide strong hedging and safe-haven properties against the US economic and trade policy uncertainties; however, DJShenzhen (DJChina88) stock shows weak hedge and safe-haven properties (hedging benefits) against Chinese trade policy uncertainty (CTPU) (Chinese economic policy uncertainty [CEPU]).Practical implicationsThe findings have significant implications for investors, portfolio managers and regulators in hedging and making proper decisions under uncertain circumstances.Originality/valueThe study extends the literature on stock market performance to cover the economic and trade policy uncertainty by providing novel evidence during the recent COVID-19 and Russia–Ukraine invasion.

Determinants of dry bulk shipping freight rates: Considering Chinese manufacturing industry and economic policy uncertainty

The past decades have witnessed the rapid development of China's manufacturing industry, which has established China's status as a manufacturing and trading power. Along with the impressive transportation volume of global trade, Chinese and global shipping markets have been further developed. Both trade volumes and freight rates will be impacted by the import-export market as well as price fluctuation. The freight rates of the dry bulk shipping market are our main concern, whether they are influenced by Chinese manufacturing industry. Moreover, the relationships between the Chinese and global shipping freight rates of dry bulk in every sub-sector are discussed by employing Vector Autoregressive (VAR) model and the least absolute shrinkage and selection operation (LASSO) regression. Besides, the effects of China's economic policy uncertainty (EPU) on freight rates are explored. Our data includes the monthly data from July 2012 to August 2021, where the development of the Chinese shipping market and manufacturing industry is represented by the Tianjin Bulk Freight Index (TBI) and China's Manufacturing Purchasing Managers' Index (PMI). We find that Chinese PMI only influences freight rates of Panamax and Capesize sub-segments of the global shipping market. Surprisingly, Chinese EPU has no meaningful effect on the freight rates of the dry bulk shipping market due to the lack of shipping characteristics. Our investigation is helpful for shipowners and operators when engaging in dry bulk shipping services and investment decision-making.

Economic policy uncertainty and price pass-through effect of exchange rate in China

Using the Chinese economic policy uncertainty (EPU) index, this paper investigates the spillover effect on the price pass-through effect of the RMB exchange rate and uncertainty, using the time-varying parameter vector autoregressive (TVP-VAR) model. We find that EPU has a significant effect on the price pass-through effect of the RMB exchange rate, which indicates that an increase in uncertainty will significantly enhance the price pass-through effect of the exchange rate. In addition, EPU itself can have a significant spillover effect on the exchange rate. Finally, the price pass-through effect of the RMB exchange rate is incomplete, and its impact on the price level gradually decreases along the circulation chain. The Chinese government should pay close attention to the impact of economic policy uncertainty on the price pass-through effect of the RMB exchange rate and the exchange rate and further strengthen the risk prevention and early warning mechanism to minimize the impact of uncertainty on China's macroeconomy.

Does the Economic Policy Uncertainty in the USA and China Affect Indian Stock Markets Symmetrically and Asymmetrically? An Empirical Analysis of Pre- and Post-Coronavirus Disease 2019 Timelines

Globalization and economic interconnections have recently garnered a lot of attention, and scholars and policymakers are delving into the effects of policy uncertainty on macroeconomic fundamentals against this backdrop, the current study investigates the symmetric and asymmetric effects of economic policy uncertainty (EPU) in the USA and China on the Indian benchmark index. Furthermore, the study also analyses the variation in results due to the occurrence of uncertain events. For the empirical analysis, non-linear autoregressive distributed lag (NARDL) and autoregressive distributed lag (ARDL) techniques have been employed, and the findings substantiate an asymmetric relationship between the US EPU and the Indian stock market, while a symmetric relationship between the Chinese EPU and the Indian stock market. The study also reveals that in the short run, the Indian stock market is immune to the fluctuations in the Chinese stock market and policy uncertainty. Moreover, the outcomes further reveal that the US and Indian stock markets project a mirror performance. In addition, the study further reveals that, unlike the pre-Coronavirus Disease 2019 (COVID-19) timeline, during the COVID-19, the short-run volatility was high between the explanatory and outcome variables. The study is an original work and offers several useful recommendations.

The stress contagion among financial markets and its determinants

ABSTRACT The purpose of this paper is to study the spillover effects of financial stress among five important financial markets (bond, stock, foreign exchange, interbank, and real estate markets) in China, and explore the important determinants of financial stress spillover level among the markets and the impact of the Chinese stress spillover situation on the European markets. Our findings are as follows: First, there is a significant stress spillover effect among the five markets, and the total financial stress spillover index (TSSI) is very high during the global financial crisis. Generally, the stock and real estate markets are the major transmitters of stress spillover, and the interbank and bond markets are the major receivers. Second, the most macro factors have significant impacts on the financial stress spillover level among the markets, especially CPI index, the Chinese economic policy uncertainty index and VIX index. And the severity of the COVID-19 epidemic in China and the world has a significant impact on the TSSI, especially from March 2020 to August 2020. Finally, the TSSI can significantly increase the volatility of French stock market, Italian stock market and German government bond market, especially during the Sino-US trade war and the COVID-19 epidemic.

Economic policy uncertainty and stock market sector time-varying spillover effect: Evidence from China

This paper investigates the volatility spillover effect among the Chinese economic policy uncertainty index, stock markets, gold and oil by employing the time-varying parameter vector autoregressive (TVP-VAR) model. Three main results are obtained. Firstly, the optional consumption, industry, public utility and financial sectors are systemically important during the sample period. Secondly, among the four policy uncertainties, the uncertainty of fiscal policy and trade policy contributes more to the spillover effect, while the uncertainty of monetary policy and exchange rate policy contributes less to the spillover effect. Thirdly, during COVID-19, oil spillovers from other sources dropped rapidly to a very low point, it also had a significant impact on the net volatility spillover of the stock market. This paper can provide policy implication for decision-makers and reasonable risk aversion methods for investors.

Economic policy uncertainty of China and investment opportunities: a tale of ASEAN stock markets

PurposeThe purpose of this paper is to examine the effect of economic policy uncertainty (EPU) of China on investment opportunities in five ASEAN economies.Design/methodology/approachThis paper employs advanced empirical approaches, such as Multivariate DCC-GARCH and Continuous Wavelet Transform (CWT) to test the research objective. The period of analysis involved monthly data from 2003 until 2019.FindingsThis paper provides evidence where the Malaysian stock market to be the least exposed to risks emanating from Chinese EPU, followed by Singapore, the Philippines, Thailand and Indonesia. Results for investment opportunities based on time horizon suggest, for a short-term holding period, investors are better off investing in Singapore and Indonesia, while, for medium-term holding periods, all ASEAN markets appear lucrative except for the Philippines.Practical implicationsFrom a managerial perspective, the outcome or findings of this study are expected to aid the retail and institutional investors in designing better strategies on diversifying a stock portfolio with different holding periods.Originality/valueTheoretically, the findings of this study contribute fresh insights into an emerging strand of literature focusing on the transmission of regional policy. Methodologically as well, this study is a novel venture to the best of authors' knowledge.