Economic policy uncertainty and the climate challenge: Moderating effects on the innovation–emissions nexus in G20 nations

This chapter determines and compares the responses of South African economic growth to positive (i) foreign economic policy uncertainties (ii) foreign GDP growth uncertainties and (iii) foreign GDP growth shocks. Does South African economic policy uncertainty act as an inward transmitter and conduit of foreign economic policy uncertainty shock to the domestic GDP growth? Do foreign GDP growth uncertainties act as transmitters and conduits of foreign economic policy uncertainty shock to the South African GDP growth? Does a combination of economic growth uncertainty and policy uncertainty impact domestic exports growth? Evidence in this chapter confirms that economic policy uncertainty tends to exert negative effects on foreign economic growth in this chapter. The negative spillover of foreign policy uncertainty results in a contraction in South African economic growth. In addition, the South African economic policy uncertainty acts as an inward transmitter and conduit of foreign economic policy uncertainty shock to domestic GDP growth. At the same time, foreign GDP growth uncertainties transmit foreign economic policy uncertainty shock to South African GDP growth. However, the big decline in the actual GDP growth than the counterfactual responses implies that South African policy uncertainty leads to the worsening in economic growth contraction following the foreign policy uncertainty shock. Furthermore, positive European GDP growth raises South African exports to the Euro area and the increases are much higher in the long run when South African policy uncertainty is shutoff than when operating in the model. This shows that the exports channel explains why South African economic growth may not benefit to the maximum from the improvement in European GDP growth impulse.

ABSTRACTIn the context of frequent trade frictions and geopolitical conflicts, the increase in economic policy uncertainty highlights the application value of digital technologies. Digital finance business development originates from applying achievements in financial technology innovation and is also rooted in specific economic policy environments. This work explores the relationship between regional economic policy uncertainty and digital finance. Using data from 2011 to 2021 across 30 Chinese regions, we discover that economic policy uncertainty positively impacts digital finance and that there is regional heterogeneity. Economic policy uncertainty effectively drives government investment. Meanwhile, government investment plays a mediating role in economic policy uncertainty and digital finance. According to the threshold regression test, economic policy uncertainty's impact on digital finance demonstrates a double threshold effect dependent on the economic development level. As economic development levels rise, the promoting role of economic policy uncertainty in digital finance gradually strengthens. Further analysis reveals that digital finance has a significant spatial positive correlation and that economic policy uncertainty can drive the development of digital finance in neighbouring areas through the spatial spillover effect. Consequently, financial institutions should actively develop digital finance to strengthen their risk resilience in the face of shocks to economic policy uncertainty. Simultaneously, the government may facilitate the orderly and healthy development of digital finance through augmenting investment, optimising the layout of digital infrastructure, and boosting interregional collaboration.

PurposeIn the past few years, numerous economic uncertainty challenges have occurred globally. These uncertainties grasp the attention of the researchers and they examine the role of economic policy uncertainties in several aspects. Therefore, this study contributes to the literature by exploring the house prices volatility and economic policy uncertainty nexus in G7 countries.Design/methodology/approachThe authors applied the newly introduced econometric technique, the GARCH-MIDAS model, to the sample size of January 1998–May 2021.FindingsThe result shows a significant relationship between house prices volatility and economic policy uncertainty. Moreover, economic policy uncertainty acts as a significant determinant of house prices volatility. In addition, the out-of-sample also shows that the economic policy uncertainty is an effective predictor and the GARCH-MIDAS has a better predictive ability.Originality/valueThis paper makes a unique contribution to the literature with reference to developed economies, being a pioneering attempt to investigate the GARCH-MIDAS model to analyze the relationship between housing prices volatility and economic policy uncertainty by applying more rigorous and advanced econometric techniques.

There is a growing interest among economists and policymakers in examining economic (policy) uncertainty and its effects on the (overall) economy. This study examines the economic (policy) uncertainty in Brazil, the most populated country in Latin America, before and during the Covid-19 crisis, which has severely affected the Brazilian economy and society. Brazil was the first country in Latin America to report a confirmed case of Covid-19. This study finds that the Covid-19 crisis has contributed to an increase in economic (policy) uncertainty in Brazil. However, the increase was (more or less) short-lived. Data show that economic uncertainty in Brazil was at its peak in April 2020 and that economic policy uncertainty in Brazil was at its peak in March 2020.

On conflict of natural resources-carbon emissions nexus in China: The role of economic policy uncertainty

The role of economic policy uncertainty in the risk transmission between crude oil and stock market cannot be ignored. However, it is unclear whether economic policy uncertainty always amplifies the impact of oil price shocks on stock market over time. This study employs the time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model to examine the dynamic relationship among different types of oil price shocks, economic policy uncertainty, and China’s stock market returns at the aggregate and industry levels. The empirical results are as follows: First, different types of oil price shocks and economic policy uncertainty have significant time-varying impacts on stock market returns, which mainly occur in the short term. During periods of increased economic policy uncertainty, the stock market is more sensitive to oil price shocks. Second, economic policy uncertainty provides a transmission channel for the propagation between oil price shocks and stock markets, but how does economic policy uncertainty connect oil-stock nexus depends on the origins of oil price shocks. Third, the response patterns of stock market to oil price shocks and economic policy uncertainty are heterogeneous in different industries. Our results provide important implications for policymakers and investors.

Spillover effects of policy uncertainty on the foreign exchange rate: Evidence from selected developed and developing countries

Analyzing the impacts of geopolitical risk and economic uncertainty on natural resources rents

Economic policy uncertainty and China’s growth-at-risk

Has Economic Policy Uncertainty Hampered the Recovery?

Has Economic Policy Uncertainty Hampered the Recovery?

Objective: Existing literature attests to the longstanding global concern regarding Economic Policy Uncertainty (EPU), recognizing its impact on economic growth, employment, and investments. Despite its acknowledged influence, studies on EPU in India have been comparatively limited. This paper addresses this gap by utilizing 83 months of data (from January 2017 to November 2023) from the recently formulated EPU Index of India and monthly closing values of the Nifty 50. The objective is to find if there is an influence of EPU on the stock markets in India. Method: The study employs correlation analysis, Ordinary Least Squares (OLS), and Quantile regressions, to investigate the relationship between EPU and the Nifty 50, representing the Indian Stock Market. Result: While overall findings indicate a low correlation, year-wise analyses reveal a notable negative correlation in specific years, notably during the COVID year. OLS and Quantile regressions further affirm a negative impact of EPU on Nifty 50, particularly evident in lower quantiles, with the effect diminishing in higher quantiles. Conclusion: The study indicates the limited effect that EPU has on the stock market. Though there is a negative association, it could be temporary and a short-term variation. Given the novelty of the EPU index and limited studies in India, this paper contributes significantly to the existing literature, particularly in the Indian context.

PurposeUnder the background of the overall increase of China's economic policy uncertainty and the urgent need for the transformation and upgrading of the substantial economy, this paper studies the time-varying causality between China's economic policy uncertainty and the growth of the substantial economy through bootstrap rolling window causality test, further refines economic policies and studies the causal differences between different types of economic policies and substantial economic growth, refining the conclusions of previous studies.Design/methodology/approachThis paper first studies the causal relationship between China's economic policy uncertainty and substantial economic growth in the full sample period through bootstrap Granger causality test. Then, the paper tests the short-term and long-term stability of the parameters of the VAR model, and it is found that the model parameters are unstable in both the short and long term, so the results of the Granger causality test of the full sample are not credible. Finally, we conduct a dynamic test of the causal relationship between China's economic policy uncertainty and substantial economic growth by means of rolling window, so as to comprehensively analyze the dynamic characteristics and sudden changes of the relationship between them.FindingsThe research shows that economic policy uncertainty in China has a significant inhibiting effect on the growth of substantial economy. Growth in the substantial economy will drive up economic policy uncertainty before 2016 and restrain it after that. In addition, this paper further subdivides economic policy uncertainty to explore the causal differences between different types of economic policy uncertainty and substantial economic growth. The test results show that the relationship between them has obvious policy heterogeneity. The fiscal policy uncertainty and the monetary policy uncertainty, as the main policy means in China, has a significant impact on the growth rate of substantial economy in multiple ranges, but the effect time is short. Although trade policy uncertainty has a significant impact on the growth rate of substantial economy only during the financial crisis, the effect lasts for a long time. The impact of exchange rate and capital account policy uncertainty on the growth rate of substantial economy is mainly reflected after 2020.Originality/valueThe values of this paper are as follows: First, the economic policy uncertainty is combined with the growth of substantial economy, which makes up the gap of previous studies. Second, the economic policy uncertainty is further subdivided. The paper explores the causal differences between different types of economic policy uncertainties and the growth of substantial economy, so as to make the research more detailed. Finally, different from the previous static analysis, this paper uses dynamic model to examine the relationship between China's economic policy uncertainty and the growth of substantial economy from a dynamic perspective, with richer research conclusions.

Purpose: This study aims to evaluate the nature of the relationship between economic policy uncertainty and industry beta and the cross-sectional heterogeneity between them. Theoretical Framework: Industry Return is derived from the annual market capitalization of each industry by taking a summation of all firms' market capitalization values to find out the industry beta variable. The categorization of 48 industries according to the Fama-French model has been defined as the industry in this study. The main explanatory variable for this research strategy is the Economic Policy Uncertainty or the EPU. Economic policy uncertainty is measured based on the given index by Baker, Bloom, and David index. Baker, Bloom, and Davis, or BBD, perceive that there are different manners by which the economic policy uncertainty can be evolved. For instance, economic policy uncertainty can be influenced by what different types of discussions related to economic policies are going to be undertaken. BBD has tried looking into the landscape regarding the economic policy uncertainty overall through the eyes of newspapers based in the USA. In addition, there has been textual analysis by Baker, Bloom, and Davis or BBD over different types of digital archives for the top 10 U.S. newspapers for obtaining the count of articles on a monthly basis for every newspaper so that they can be able to focus on the specific economic policy uncertainty. Methodology: Positivist research philosophy has been implicated in conducting this research study. From the research approach perspective, the deductive research approach has been implemented. In addition, a quantitative research strategy has been used for modeling purposes and explanation. Furthermore, an experimental research design has been incorporated into this research strategy. The required data set has been gathered from secondary sources, including the WRDS and BBD databases. Industry return has been calculated based on industry market capitalization. From a modeling perspective, a baseline time series regression model has been incorporated. In this research conduction, there has been an analysis of 10 U.S. industries. The time span is from 2000 to 2020. In addition, there has been an analysis of different policy uncertainties based on the decomposition of EPU. Results & Conclusion: First, the impact of the economic policy uncertainty in the combined form on the industry-level betas has been analyzed. In this case, the entire time scale of 19 years has been divided into three classes: the financial turmoil period from 2001 to 2006, the financial turmoil period from 2007 to 2010, and finally, the financial turmoil period from 2011 to 2020. It has been pointed out that overall, there has been a statistically significant positive impact of economic policy uncertainty on industry level-betas mostly on all industries. In addition, when there has been a decomposition of the economic policy uncertainty index, a statistically significant positive association has been found regarding monetary policy uncertainty and fiscal policy uncertainty. Originality: The significance of this research is that there has been a one-to-one relationship finding on the impact of EPU on industry-level beta. Very few literatures have covered this issue broadly. One notable literature on this topic was conducted by Yu et al. in 2017. However, this research study has analyzed another ten industries in North America that have not been previously analyzed. In addition, for deep insight, the research framework has been divided into three parts: overall period analysis, pre-financial crisis turmoil, and post-financial crisis turmoil periods. In addition, there has been an analysis of the impact of component-wise seven policy uncertainty index on industry-level beta. Contribution: Different factors, including macroeconomic phenomena, can influence industry-level beta or systematic risk. In recent times, economic policy uncertainty analysis has become inevitable for measuring the policy implications and their impacts on industry-level risk to determine their dynamics. The relationship between the economic policy uncertainty index and the industrial structural model of risk dynamics has been established by this research study.

Economic Policy Uncertainty and Household Inflation Uncertainty