Trade Policy Uncertainty Research Articles

The Impact of Trade Policy Uncertainty on the Domestic Technological Content of Export Products : Evidence from Chinese Manufacturing Firms

The Impact of Trade Policy Uncertainty on the Domestic Technological Content of Export Products : Evidence from Chinese Manufacturing Firms

Trade under Trade Policy Uncertainty: The Moderating Roles of US Preferential Trade Agreements and Their Heterogenous Effects.

Trade under Trade Policy Uncertainty: The Moderating Roles of US Preferential Trade Agreements and Their Heterogenous Effects.

An import(ant) price of Brexit uncertainty

We estimate the impact of trade policy uncertainty (TPU) on CES import price indices, focusing on the implications of Britain’s exit from the European Union (Brexit). Our analysis reveals that a higher probability of Brexit increases U.K. import price indices by raising the prices of existing products and reducing product variety from the E.U. We find evidence that the risk of higher import protection from the 2016 referendum increased current import price indices by 11 log points. This amounted to a 2 log point increase in manufactured goods prices and a 0.6 log point decrease in consumers’ real income.

Can Trade Policy Uncertainty Drive Green Innovation? Empirical Evidence From the US–China Trade War

ABSTRACTChina's rapid economic growth in recent years has coincided with heightened environmental regulations and an upsurge in greenhouse gas emissions, necessitating a greater emphasis on green innovation to mitigate environmental risks. Concurrently, the US–China trade war has elevated trade policy uncertainty (TPU). This study uses the TPU surge from the trade war as a quasi‐natural experiment, employing text analysis of annual reports to assess firms' TPU perceptions. Using a difference‐in‐differences method, we find that increased TPU significantly hinders green innovation. Firms' responses vary with environmental advantages, regulation levels, and government subsidies. Mechanisms include reduced environmental investment, decreased executive attention to environmental issues, and corporate social responsibility. These findings underscore the importance of a stable trading environment for promoting green innovation.

Natural resources and sustainable development: Evidence from the dynamic correlation between crude oil and gold market

Amidst the uncertainty in markets spurred by globalization and technological advancements, the volatility of the crude oil and gold markets, which are emblematic of natural resource markets (NRMs), profoundly impacts global economic sustainability. This study innovatively quantifies and contrasts the impact of macroeconomic uncertainty factors on the volatility and dynamic correlation of these pivotal NRMs by extending the GJR-GARCH-MIDAS-X and DCC-MIDAS-RC-X models grounded in global economic policy uncertainty (GEPU), trade policy uncertainty (TPU), monetary policy uncertainty (MPU), and geopolitical risk (GPR). Concurrently, employing principal component analysis (PCA) blends numerous uncertainty factors, heightening the models’ explanatory capacity and predictive precision. Empirical findings suggest that all uncertainty factors exert significant positive effects on both crude oil and gold volatility, albeit with heterogeneity. Furthermore, the correlation between crude oil and gold fluctuates over time under the influence of uncertainty factors. Additionally, this study revealed asymmetric effects on realized volatility between the two NRMs. This research not only provides novel theoretical insights and empirical evidence concerning the intricate dynamic interplay between the two NRMs, but also has significant ramifications for policymakers, market regulators, and investors in crafting effective strategies and decisions amidst market uncertainty.

Trading in Turbulent Times: Unravelling the Interplay between Trade Policy Uncertainty and Geopolitics in Russian Mineral Resource Supply

Trade policy plays a pivotal role in shaping import and export volumes within the global economy. However, the escalation of geopolitical tensions has posed significant challenges to the smooth flow of mineral resource trade. This study aims to analyse the consequences of global trade policy uncertainty (TPU) and various measures of geopolitical risk (GPR), including terror threats, war threats and nuclear threats (NCT), on Russian mineral exports (MEX). The analysis covers the period from January 2013 to December 2021. By employing sophisticated quantile regression methodologies, such as the cross-quantilogram (CQ) and cross-spectral quantile coherency (CQC) techniques, this study uncovers a compelling interaction between TPU and Russian MEX across different market conditions. Interestingly, TPU exerts a significantly positive impact on the export volumes of Russian mineral resources. In contrast, the presence of GPRs, particularly warfare and terrorism, proves to be detrimental to MEX during bullish market phases across various memory horizons. Surprisingly, NCT stimulates mineral trade during bearish market conditions, both in monthly and annual timeframes. These findings remain robust and consistent even when the CQC technique is employed. In light of these pressing geopolitical challenges, this study underscores the importance of developing sustainable mineral trade policies that foster enhanced global cohesion. It is crucial to address these challenges effectively to ensure the smooth and efficient flow of mineral resources in the international trade landscape. JEL Codes: C22, F13, F14, P28, Q21, Q27

Forest Products Trade and Sustainable Development in China and the USA: Do Bioenergy and Economic Policy Uncertainty Matter?

The United Nations Agenda 2030 for Sustainable Development has induced the empirics to find the factors that can contribute to sustainable development. However, limited empirical evidence has estimated the impact of forest trade, bioenergy, and economic policy uncertainty on sustainable development. This study fills the gap by analyzing the impact of forest trade, bioenergy, and economic policy uncertainty on sustainable development in China and the USA using the ARDL and QARDL approaches. The findings of the ARDL model suggest that forest trade helps boost both short- and long-run sustainable development in China and the USA, while bioenergy fosters sustainable development in the short and long run only in China and in the USA, bioenergy improves sustainable development only in the long run. In contrast, economic policy uncertainty hurts sustainable development in the short and long run in China, while in the USA, only the long-run negative association between the two variables is observed. Thus, policymakers in China and the USA need to focus on enhancing trade in forest products, fostering bioenergy generation, and reducing uncertainties in economic policy to promote sustainable development.

The Effect of Trade Policy Uncertainty on Green Technology Innovation: Evidence from China’s Enterprises

Promoting green technology innovation is essential for sustainable development and the transition to a low-carbon economy. Using data from listed manufacturing companies in China from 2000 to 2020, this paper takes the establishment of permanent normal trade relations with the United States after China’s accession to the WTO as a quasi-natural experiment and uses the difference-in-differences method to study the impact of the decline in trade policy uncertainty on firms’ green technology innovation. The results show the following: (1) Reduced trade policy uncertainty significantly enhances green technology innovation in firms. (2) Further research finds that the decline in trade policy uncertainty mainly promotes the level of the green technology innovation of firms by alleviating financing constraints faced by firms and intensifying market competition. (3) A heterogeneity analysis reveals that the impact is more pronounced in firms with lower capital intensity, higher growth, export firms, and firms exporting to the United States. This study offers micro-level empirical evidence from China on the economic outcomes of external trade policy changes from the perspective of firms’ green technology innovation and provides insights into how the government should respond to the risks of external trade frictions and improve firms’ sustainable development in the future.

Trade Policy Uncertainty, Financing Constraints, and Firm Innovation: Evidence from China

Trade Policy Uncertainty, Financing Constraints, and Firm Innovation: Evidence from China

Unraveling the impact of financial stress and trade policy uncertainty on advancing renewable energy transition in the USA

Renewable energy consumption (REC) has become the most suitable option to tackle the issues of energy security and climate change because it is a sustainable, clean, and affordable energy source. Literature on the determinants of REC is growing rapidly, but most rely on linear analysis. This analysis is a nonlinear perspective on the impact of financial stress and trade policy uncertainty on REC in the USA over 1995Q1-2021Q4. The study uses autoregressive distributed lag and nonlinear autoregressive distributed lag for empirical analysis. The linear estimates reveal that financial stress and trade policy uncertainty reduce long-run (LR) REC. On the other hand, the nonlinear estimates suggest that positive changes in financial stress and trade policy uncertainty reduce REC, whereas the negative changes in both these factors boost REC in the LR. While the GDP causes an improvement in REC, environmental technologies do not significantly impact the REC in the LR. In the short-run, only the linear and nonlinear estimates of financial stress and environmental technologies significantly impact REC. Due to the asymmetric nature of the findings, policymakers must take into account the positive and negative changes in the financial stress and trade policy uncertainty while devising policies to promote renewable energy transition.

The asymmetric and time-varying effects of trade policy uncertainty on the insurance premiums in China: Evidence from cross-quantilogram

This study investigates the asymmetric and time-varying effects of trade policy uncertainty (TPU) on China's insurance premiums by applying the bivariate cross-quantilogram approach across different quantiles of TPU. The results suggested that the impacts of TPU on the insurance market are different across different quantiles of TPU, indicating an asymmetric effect. Besides, the effect of TPU on insurance markets is time-varying when considering different time horizons ranging from 1 to 24 months. In the short run, TPU negatively impacts the insurance market, while, in the long run, insurance premiums increase with the increase of TPU.

Does trade policy uncertainty hurt renewable energy-related sustainable development goals in China?

Trade policy uncertainty might hamper trade flow, including the trade of green and renewable energy technologies. Therefore, this study aims to examine the asymmetric effects of trade policy uncertainty (TPU) on renewable energy consumption (REC) in China. To calculate the short- and long-term relationships between REC, TPU, national income, carbon footprints, and financial development, we used the nonlinear QARDL technique. The estimates reveal that an upsurge in TPU hurts REC in the short and long run. Conversely, a stable trade policy or a reduction in TPU increases REC in the long run. In the short run, a fall in TPU exerts no influence on REC. The findings further imply that various factors, including GDP, CO2 emissions, and financial development, contribute to long-term improvements in REC in China, both in the short and long run.

Trade policy uncertainty and capacity utilisation rate: Firm‐level evidence from China's WTO accession

AbstractThis paper was one of the first to explore the impact of trade policy uncertainty (TPU) reduction on Chinese firm capacity utilisation rate from the perspective of trade policy variation. Based on a quasi‐natural experiment of the implementation of Permanent Normal Trade Relation (PNTR) after China's WTO accession, this paper adopts the difference‐in‐difference (DID) method to conduct empirical analysis, and finds that reduction in TPU significantly raises firm capacity utilisation rate. The mechanism tests show that export expansion is an important channel through which reduction in TPU raises firm capacity utilisation rate, especially for firms exporting to the United States; reduction in TPU also raises firm capacity utilisation rate through the improvement of production efficiency; in addition, reduction in TPU raises firm capacity utilisation rate along the downstream linkages, whereas the effect of the upstream linkages is insignificant. Finally, this paper takes a step further to conduct empirical analysis at industry level, the results show that reduction in TPU also significantly raises manufacturing aggregate capacity utilisation rate, and the improvement of resource reallocation efficiency (especially the exit of the firms with backward production capacity) plays an important role. Our study was helpful to understand the driving forces of the changes in Chinese manufacturing capacity utilisation rate in recent years, and it also provides new ideas for solving over‐capacity.

Research on safe-haven currencies under global uncertainty —A new perception based on the East Asian market

The backdrop of this research is the high global uncertainty that has amplified the demand for safe-haven assets, particularly in the East Asian market. This paper redefines the concept of a “safe-haven” currency to align with contemporary geopolitical and trade policy uncertainties, diverging from the traditional volatility index (VIX) risk measure. We investigate the risk aversion properties of East Asian currencies under these nonmarket risks using dynamic heterogeneous panel data analysis and robustness checks with double machine learning. Empirical results reveal that no East Asian currency qualifies as a safe haven under geopolitical risk and trade policy uncertainty. However, the Japanese yen (JPY) maintains its status under the VIX indicator. This study highlights the insufficiency of traditional safe havens like the JPY and underscores the importance of considering nonmarket risks, challenging the effectiveness of traditional investment strategies amid modern geopolitical and policy uncertainties. The findings suggest that investors should prioritize nonmarket risks and call for reform in the global monetary system to enhance currency resilience. The novel methodological approach to evaluating safe-haven currencies addresses the need for diversified currency portfolios to mitigate nonmarket risks.

US trade policy and the US dollar

We show that the US dollar response to trade policy uncertainty (TPU) is key to assessing the impact of US trade policy. Employing structural vector autoregressive models, we find that TPU shocks supported a multilateral USD appreciation during the 2018–19 trade tensions between the US and some of its major trading partners. We rationalize this in a two-country New Keynesian model with financial frictions that links the increase in TPU to rising demand for safe USD assets. Our findings suggest that the TPU-induced appreciation of the USD in 2018–19 significantly counteracted US trade policy attempts to raise US competitiveness.

Extreme weather, policy uncertainty, and risk spillovers between energy, financial, and carbon markets

Extreme weather, as well as policy uncertainties associated with climate change, have fueled global energy market turbulence and cross-market risk contagion, which have had serious effects on the economy. Using time-frequency network analysis based on quantile vector autoregression (QVAR), this study reveals the risk spillovers between China's energy, financial, and carbon markets in different time and frequency domains. The effects of extreme weather and policy uncertainty on market risk spillovers are also examined. The results show that: (1) Risk spillovers vary significantly in different time and frequency domains, and extreme risks tend to occur in the tails of the shock distribution, and market risk spillovers occur mainly in the long term; (2) Extreme weather and policy uncertainty significantly affect energy, financial, and carbon markets, altering their net spillover levels. Among which the coal market is the most volatile and highly sensitive to changes in external conditions; (3) Risk spillovers exhibit distinct time-varying characteristics, with extreme weather, climate policy uncertainty, and trade policy uncertainty exacerbating market risk spillovers. These findings could serve as a reference for monitoring market risk spillovers, facilitating energy transition, and achieving dual‑carbon targets.

Quantile-based extended joint connectedness between trade policy uncertainty and Gulf Cooperation Council Islamic sectoral volatility

This study quantifies the shock transmission mechanism between the trade policy uncertainty (TPU) index and Sharia-compliant stock sectoral conditional volatility in the Gulf Cooperation Council (GCC) countries. We employ a comprehensive analysis that includes the time-domain extended joint and frequency-domain quantum vector autoregressive (QVAR) frameworks. The time-domain QVAR demonstrates that TPU causes the most substantial shocks to utility sector volatility. Investors in the GCC must strategically allocate their investment portfolios to the consumer services and energy industries, which are less vulnerable to the TPU shock. The results show that TPU shocks provide more error variances to the long-term and bullish conditional volatility (or higher quantiles) of the utility, real estate investment trust funds (REIT), healthcare, and industry sectors. Conversely, during bearish volatility conditions (lower quantiles), TPU shocks result in higher shocks in the conditional volatility of the utility, REIT, finance, and industrial sectors. Long-term investors should diversify their portfolios to mitigate risk in the utility, REIT, and industry sectors through strategic investments in consumer service sector. However, in the short term and during both bearish and bullish sectoral volatility, the consumer service and industry sectors are more vulnerable to TPU shocks. Regarding diversity, the REIT, energy, and financial sectors are the least affected by TPU shocks, offering a protective buffer in the short term and during periods of higher and lower GCC Islamic sectoral volatility.

Trade Balance, Real Exchange Rate and Trade Policy Uncertainty in Türkiye: Evidence from the SVAR Approach

Trade Balance, Real Exchange Rate and Trade Policy Uncertainty in Türkiye: Evidence from the SVAR Approach

Partisan conflict, trade policy uncertainty, and the energy market

This paper investigates the time-varying effects of partisan conflict (PC) and trade policy uncertainty (TPU) on the energy market from January 2000 to July 2021 by employing a time-varying parameter vector autoregressive model with stochastic volatility. The results show that the pass-through effects of the PC and TPU shocks on energy return and volatility varied over time and are different across energy sub-sectors. PC and TPU had a greater impact on energy market return in the short-term, whereas the impact on energy market volatility was spread across relatively long periods. Generally, the impact of TPU on energy return and volatility was greater than that of PC at different lag periods and different points. Further, under different energy frameworks, the trend of the time-varying relationship between PC and TPU was roughly the same, indicating the robustness of our results.

The nexus between natural resource development, trade policy uncertainty, financial technology and poverty in China: Contributing to the realization of SDG 1

Population poverty inhibits China's economic growth. Reducing poverty in the face of risk and uncertainty has been a priority for the Chinese government in recent years. And it is an important part of realizing the Sustainable Development Goal 1. The paper first uses entropy method and TOPSIS to comprehensively evaluate the Financial Technology (Fintech) index. This paper uses the autoregressive distributed lag (ARDL) bounds test to measure the long-term relationship. This paper also uses a nonlinear autoregressive distributed lag (NARDL) model to examine the asymmetric impact of trade policy uncertainty (TPU), natural resource development (NRD) and fintech on poverty reduction. For the robustness of the model, this paper uses three parametric methods FMOLS, DOLS and CCR. The findings of this paper are as follows. Increases or decreases in TPU can have a negative impact on poverty reduction. It brings greater impact when it increases. A reduction in the level of NRD and an increase in the fintech index will promote poverty reduction policies. An increase in the level of NRD and a decrease in the fintech index have opposite effects. The results of FMOLS, DOLS and CCR support these conclusions. The findings of this research provide effective suggestions for the formulation of future poverty eradication policies and the promotion of fintech development in China.