Time-varying Parameter Structural Vector Autoregression Research Articles

Exploring the dynamic connections between oil price shocks and bond yields in developed nations: A TVP-SVAR-SV approach

This paper investigates the impact of oil price changes on bond yields across nine developed nations, focusing on how demand, supply, and oil-specific demand shocks influence bond spreads. Using a Time-Varying Parameter Structural Vector Autoregression with Stochastic Volatility (TVP-SVAR-SV) model, we find that bond yields are short-term responsive to oil price fluctuations, indicating efficient domestic bond markets. However, we observe distinct country-specific reactions, particularly in the US and the UK. In the US, supply shocks cause temporary declines in bond yields, while demand shocks reduce bond yields in both countries. Oil-specific demand shocks have cyclical impacts. Unlike the global financial crisis, the COVID-19 pandemic uniquely influenced bond yields, with minimal short-term effects in Canada, France, Spain, and the US post-COVID-19, contrasting with the severe impacts during the financial crisis. These findings suggest investors should consider the varying impact of oil shocks on bond yields across countries, and policymakers should monitor and address the potential implications of oil price fluctuations for financial stability and market efficiency.

The ability of energy commodities to hedge the dynamic risk of epidemic black swans

The outbreak of COVID-19 increased global financial risks and economic shocks. Although epidemic risk is on the decline, the likeliness of a similar black swan event occurring in the future cannot be ruled out. In this study, we constructed epidemic search indices using the Google Search Volume Index (SVI) to examine whether investor sentiment regarding the COVID-19 pandemic affected stocks, gold, silver, copper, crude oil, and natural gas. The results reveal that, over the entire epidemic period, energy assets (crude oil and natural gas) were the most “resistant” to epidemic panic, making them suitable for hedging the risk associated with epidemic panic risk. We employed a time-varying parameter structural vector autoregression model with stochastic volatility (TVP-SVAR-SV) to analyze the time-varying contagion effects of epidemic search indices on various asset prices at different points in time. The findings indicate that in the early stages of the COVID-19 pandemic when epidemic panic risk was highest, natural gas prices exhibited the most risk-averse characteristics. Only during the middle to later stages of the epidemic did natural gas prices begin to be positively affected by epidemic panic sentiment. However, during this period, the epidemic search indices show a stable declining trend, indicating a reduction in risk. We observe that natural gas prices only reflected panic sentiment during periods of stability. The results of this study suggest that energy commodities, especially natural gas, are suitable for hedging against unforeseen high epidemic risks. When epidemic risk decreases, profits can be realized and reinvested in assets with a higher contagion effect due to epidemic risks, further benefiting from the rebound in the prices of these assets. In addition to explaining why energy commodities are particularly suitable for mitigating epidemic-related black swan events, we provide a detailed investment strategy for hedging future epidemic risk and further elaborate on how investors should dynamically adjust their portfolios according to the severity of the epidemic and whether it is under control.

Dynamics between FinTech and financial market: Supply-driven or Demand-guided?

<p>This paper examined the dynamic relationship between FinTech development and financial development using the time-varying parameter structural vector autoregression (TVP-SV-VAR) model to analyze their impulse response relationship. The results showed that the impact of FinTech development on financial development varies across different periods. In China, before the first half of 2021, financial development mainly drove FinTech development through demand. Afterward, FinTech development promoted financial development by providing new technological tools and services. In the United States, FinTech innovation and application mainly influenced financial development through supply-driven mechanisms. After the second half of 2022, as FinTech infrastructure improved, its positive impact on the financial market strengthened. The study also found that the effects of policy changes and market fluctuations on impulse responses at specific time points differed even in countries with different systems. The findings of this paper provide valuable insights for policymakers to address the challenges and opportunities brought on by FinTech.</p>

On the transmission of oil supply and demand shocks to CO2 emissions in the US by considering uncertainty: A time-varying perspective

In an economic context increasingly governed by structural changes, crises, and uncertainty, our understanding of the transmission of oil price shocks to real economic activity and the resulting effects on CO2 emissions is found to evolve over time. Our understanding is also found to evolve when considering the sources of oil price fluctuations as emanating from the supply or demand side. So far, there is still few answers provided by the literature on how economic and policy uncertainty influences the response of CO2 emissions to different sources of oil price shocks. This paper tries to investigate this ‘missing link’ by estimating the time-varying transmission of oil supply and demand shocks to CO2 emissions in the US, while considering the simultaneous effect of uncertainty. Using monthly data covering a period including the Covid-19 health crisis, a two-step estimation procedure is adopted: before constructing a time-varying parameter structural vector autoregression model with stochastic volatility (TVP-SVAR-SV), a structural VAR model (SVAR) is implemented to decompose oil price shocks in four structural shocks namely: oil supply shock, aggregate demand shock, domestic demand shock and oil-specific demand shock. Estimation results and robustness tests show that the level of uncertainty shapes the transmission of oil price shocks to CO2 emissions. Oil supply and oil-specific demand shocks impact negatively CO2 emissions mostly when uncertainty is low. A high uncertainty level leads to a perverse positive impact of aggregate demand shocks on CO2 emissions. Interestingly, CO2 emissions are found to increase during low levels of uncertainty in response to domestic demand driven oil price shocks. This finding may be due to the expansive economic policies enforced to decrease uncertainty and increase consumption in reaction to domestic demand shocks. These results imply that workable solutions targeting an optimal level of CO2 emissions should not only consider different sources of oil price fluctuations but also the level of uncertainty. Discarding the level of uncertainty may lead to a sub-optimal calibration of the regulatory and fiscal measures aiming to protect the environment against different sources of oil price shocks and to adapt these measures to the time horizon of carbon emissions responses.

How does China's crude oil futures affect the crude oil prices at home and abroad? Evidence from the cross-market exchange rate spillovers

This study explores the cross-market relations among the prices of China's crude oil futures launched by the Shanghai International Energy Exchange (INE), China's domestic and foreign crude oil spots, and the USD against the RMB (USD/CNY) exchange rate. We emphasize the research of whether and how the RMB-denominated INE crude oil futures affect the exchange rate spillovers to China's domestic and foreign crude oil markets. With the construction of a theoretical framework and a Time-varying Parameter Structural Vector Autoregression Model with Stochastic Volatility (SV-TVP-SVAR) model, we find that: (1) The INE crude oil futures prices have close linkages with China's domestic crude oil spot prices but have insignificant and unstable spillovers on international crude oil prices, indicating that INE crude oil futures still have limited outward influence. (2) More importantly, the oil price-exchange rate nexus is diversified under different crude oil pricing currencies. The USD/CNY exchange rate shocks have negative spillovers on international crude oil denominated by USD while having positive spillover effects on INE crude oil futures denominated by RMB. (3) The USD/CNY exchange rate also positively influences China's domestic spot market via the spillovers of INE crude oil futures.

The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach

We use the time-varying parameter structural vector autoregression stochastic volatility (TVP-SVAR-SV) and causality-in-quantiles methods to explore the linkage between market liquidity and efficiency in the European Union Emissions Trading Scheme (EU ETS) during Phase III. Our findings indicate that two-way causality existed under normal and lower market conditions. Additionally, the linkage between liquidity and efficiency exhibits time-varying characteristics. Except in cases of extremely high market liquidity, the pass-through effect of liquidity on efficiency is mostly positive in the long run. The linkage is particularly stronger in the medium and long term. However, the response of liquidity to efficiency shocks is more complicated. Market efficiency generally has an overall inhibitory effect on liquidity in the short term and a promoting effect in the medium and long term. Furthermore, we investigate the impulse response during the COVID-19 period and the war between Russia and Ukraine and find that improvements in efficiency will permanently damage liquidity. Overall, the abilities of market makers and arbitrage traders, impacted by multiple factors, play an important role in the process by which liquidity affects market efficiency. By revealing and explaining the dynamic relationship between liquidity and efficiency, this research provides valuable information for policymakers and various market participants.

Time-Varying Elasticity of Cyclically Adjusted Primary Balance and Effect of Fiscal Consolidation on Domestic Government Debt in South Africa

This paper investigates the impact of the time-varying elasticity of the cyclically adjusted primary balance (CAPB) and fiscal consolidation on government debt. The time-varying parameter structural vector autoregression (TVP-VAR) model is used on a time series of data from 1979 to 2022. The contribution of this paper is on the understanding of the impact of fiscal consolidation on domestic government debt and the need to use time-varying elasticity when calculating the cyclical adjusted primary balance to provide a more accurate representation of discretionary actions taken by fiscal authorities. It is found that there is more variation in the CAPB with time-varying elasticity than with constant elasticity. Constant elasticity is not effective in capturing fiscal consolidation episodes, and time-varying elasticity is a better alternative. There is evidence that fiscal consolidation increases domestic government debt. The shocks of fiscal consolidation through government expenditure cuts reduce domestic government debt in the long run, while taxes increase domestic government debt. It is recommended that fiscal authorities use fiscal consolidation to reduce government expenditure that is related to inefficient expenditure. In the event of government expenditure, this expenditure needs to be in productive sectors of the economy that will bring about an increase in revenue rather than an increase in the tax rate. Given the result, a tax increase should be something that fiscal authorities are not using in the effort to stimulate economic growth or reduce domestic government debt.

Impact of Money Supply in Different States of Inflation and Economic Growth in South Africa

This paper investigates the impact of the money supply in different states of inflation and economic growth in South Africa from 1990 to 2021. The term “states” defines periods of low and high rates of economic variables of interest. Markov-switching dynamic regression (MSDRM) and time-varying parameter structural vector autoregression (TVP-VAR) are used in this paper. The contribution of this paper is not only based on the long run but also on the examination of the impact of the money supply in different states of inflation and economic growth. Moreover, the use of shock accounts for time-varying elasticity. It is found that there is a 0.70% decrease in the gross domestic product for a 1% increase in money supply in state 1, while in state 2, the money supply was insignificant. The money supply had a negative and a positive impact on inflation in states 1 and 2, with rates of 0.05% and 0.35% in the respective states. The money supply had a high multiplier effect on gross domestic product and inflation. More than 5 years were spent in each state for both gross domestic product and inflation, while the transition probability of moving and returning to each state is significant. The trade-off of using the money supply for economic growth and inflation is evident in South Africa. It is recommended that the state of the economy be considered when using the money supply in an effort to stimulate economic growth or stabilise inflation.

Great moderation with Chinese characteristics: Uncovering the role of monetary policy

This paper examines the contribution of multiple monetary policy instruments in explaining China's enhanced macroeconomic stability with time-varying parameter structural vector autoregression models. Our analysis is novel since existing literature primarily investigates the role of interest rates in the Great Moderation phenomenon in advanced economies, neglecting the potential impact of alternative monetary policy tools on similar episodes in emerging economies. We find that both quantity- and interest rate-based monetary policy instruments have been actively used to moderate macroeconomic fluctuations, with the efficacy of short-term interest rates increasing and required reserve ratio and money growth decreasing. However, these instruments on average account for a modest fraction of output and inflation variability over the estimation period. Moreover, systematic monetary policy has recently become more inflation-averse, but it still violates the Taylor principle. Therefore, while China's shift towards an interest rate-based policy framework is commendable, it remains incomplete.

Time-varying impacts of oil price shocks on China’s stock market under economic policy uncertainty

ABSTRACT 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.

The Dynamic Effects of Oil Price Shocks on Exchange Rates—From a Time-Varying Perspective

This study investigates the time-varying effects of three types of oil price shocks (oil demand, supply, and risk shock) on exchange rates by applying the time-varying parameter structural vector autoregression stochastic volatility (TVP-SVAR-SV) model. Through examining the impulse response of exchange rates to oil price shocks at different lag periods and time points, this paper contributes to the existing literature on the dynamic relationship between oil shocks and exchange rates. From the response at different lag periods, we find that oil price shocks have a significant time-varying impact on the exchange rate, among which oil demand shock has the most significant effect. The response of the exchange rate market to oil price shock shows an obvious short-term time-varying effect and is positive and negative alternately, with a certain periodicity. From the response at different time points, the time-varying effect of oil price shock on exchange rates is related to external shock, and is more intense during the global economic and political turmoil. This is the first empirical study using a novel method to examine the time-varying effects of oil price shock from different sources on exchange rates, providing investors and policy makers assistance to manage foreign exchange during global turmoil periods.

Time-varying effect of uncertainty shocks on unemployment

We examine the dynamic effects of uncertainty shocks on unemployment during recessions in the US. We estimate a Bayesian time-varying parameter structural vector autoregression. We analyze how the impact of uncertainty shocks on U.S. unemployment changes over time. We find that uncertainty shocks have both higher unit impact and higher total effect on unemployment during the Great Recession compared to those of previous recessions. Different characteristics of the Great Recession amplify the effect of uncertainty on unemployment. Two channels distinguish the Great Recession from other recessions: the federal funds rate hitting the zero lower bound and financial frictions. We find that these factors are significant determinants of the time-varying relationship between unemployment and uncertainty. Robustness analyses with alternative measures of uncertainty and alternative empirical specifications validate the results of the paper. • Uncertainty significantly affects US unemployment. • The effect of uncertainty on unemployment varies over time. • The effect is substantially higher during the Great Recession. • The zero lower bound and financial frictions are among the causes of time-varying effect.

The time-varying responses of financial intermediation and inflation to oil supply and demand shocks in the US: Evidence from Bayesian TVP-SVAR-SV approach

The perception of the pass-through of oil price shocks on the real and financial spheres has undergone considerable evolution with the emergence of a literature devoted to the sources of oil price fluctuations. This perception is also found to evolve over time depending on market expectations, structural changes or crises. Focusing on the specific case of the US, this paper investigates the time-varying effects of oil price shocks on financial intermediation (credit market) and inflation as a transmission channel. Monthly data are used for a period that encompasses the recent Covid-19 pandemic crisis. Prior to the construction of a time-varying parameter structural vector autoregression stochastic volatility (TVP-SVAR-SV), a structural VAR (SVAR) model is estimated to disentangle oil price shocks in four shocks: oil supply, aggregate demand, domestic demand and oil-specific demand shocks. The results underscore the increasing response of financial intermediation to oil supply, aggregate demand and oil specific demand shocks since the shale revolution. In addition, the response of credit markets to aggregate demand shocks during the covid-19 pandemic is different from that observed during the subprime crisis. It appears also that the response of inflation influence the reaction of the credit market to aggregate and domestic demand shocks.

Time-varying impact of political risk on copper prices

Using the International Country Risk Guide (ICRG) index to represent countries' political risk, the time-varying effect of political risk on copper prices was examined based on the time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model. The empirical results show that the impact of political risk on copper prices is time-varying and has tended to increase gradually in recent years. There are significant country-level differences in the impact of political risk on copper prices. Political risk has a stronger and longer-lasting impact on copper prices in exporting countries. In terms of risk sources, external and internal conflicts contribute most to international copper price fluctuations in the sample period. The impact of political risk on copper prices reaches an extreme level during the international financial crisis, the European debt crisis, and the election of Donald Trump.

Heterogeneous determinants of the exchange rate market in China with structural breaks

ABSTRACT This paper identifies a structural break in exchange rate returns from July 2005 to May 2020 using the iterated cumulative sums of squares (ICSS) algorithm. Then we explore the changing effect of determinants on exchange rates based on the time-varying parameter structural Vector AutoRegression (TVP-SVAR) model. Empirically, we find a single break based on exchange rate returns and caused by regime reform. Further analysis suggests a significant change in the shocks to inflation, foreign exchange reserves, oil prices, and short-term interest rates. In addition, the domestic and international determinants of exchange rates are heterogeneous over different periods in the short and long run. In the short run, the relation between exchange rates and inflation, the interest rate, foreign exchange reserves, and oil price, is significantly negative before August 2015. However, since August 2015, the relationship between inflation and exchange rates in China has been positive. Only short-term interest rates are affected by structural changes. This study can guide policy makers in formulating the appropriate exchange rate regime to attain sustainable market efficiency over the long run.

Time-varying effect of international iron ore price on China’s inflation: A complete price chain with TVP-SVAR-SV model

This paper employs a time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model to examine the time-varying impacts of three types of international iron ore price shocks (the supply, special demand and global demand shock) on China’s inflation from a complete price chain perspective. The empirical results indicate that: (1) demand shocks rather than supply shock in iron ore price have strong effects on China’s inflation at each stage, revealing the importance of distinguishing the underlying sources of price shifts; (2) the effects of iron ore price shocks on China’s inflation at the import stage are substantial and gradually decrease along the price chain. Meanwhile, the product prices of upstream industries are greatly influenced by price shocks, but downstream companies fail to shift rising costs to consumers due to demand elasticity; (3) the fluctuations of iron ore price are not driven by China’s inflation or supply but rather by demand factors, which is in line with the theory of super cycle. Based on the findings, policies focusing on decreasing preventive demand should be proposed. Moreover, China ought to increase overseas investment and improve utilization rates of scrap and iron ore to ease imported inflationary pressures.

Uncovering the Dynamic Relationship between Credit and Sustainable Economic Growth in Selected CEE Countries

Establishing a functional financial sector has been one of the pillars of transition to a functional market economy over the last three decades in the CEE region. The present paper provides a comprehensive analysis of the relationship between credit and economic growth in selected CEE countries, namely, Czechia, Romania, Poland and Hungary, aiming to answer questions related to (i) the role of the banking sector in fostering sustainable economic growth and the causality direction between the financial and real sector, (ii) the relationship between consumption and investment and certain categories of loans and (iii) the identification of loan supply shocks and their role in explaining the dynamics associated with other macroeconomic variables. Using a time-varying parameter structural vector autoregression model with stochastic volatility (TVP-SVAR) and sign restrictions, we identify a non-financial corporations (NFC) credit supply shock and an investment shock. Potential policy solutions to ensure a sound contribution of the financial sector to economic growth in the analyzed economies relate to the strong relationship identified between the two variables. From this perspective, the study is among the first to employ a robust dynamic framework for assessing the role of the financial sector in fostering sustainable economic growth in European emerging market economies.

How Does Capital Account Liberalization Affect Systemic Financial Risks? Evidence from China

Capital account liberalization typically results in higher volumes of capital inflows and outflows for a country, yet abnormal cross-border capital flows may lead to overall financial risk accumulation, in turn causing tremendous damages to the economy. Using a time-varying parameter structural vector autoregression model with stochastic volatility (SV-TVP-SVAR), we identify time-varying effects of capital account liberalization on four types of systemic financial risks in China. Empirical results demonstrate that capital account liberalization, in the short run, can effectively curb the accumulation of macroeconomic and sudden stop risks. On the other hand, capital account liberalization may heighten credit crunch and asset bubble risks to varying degrees. We also find that some important capital account liberalization measures are double-edged: reform policies are likely to increase macroeconomic risk when optimizing the financing structure and reducing credit crunch risk.

The time-varying effects of financial and geopolitical uncertainties on commodity market dynamics: A TVP-SVAR-SV analysis

We explore the time-varying effects of financial and geopolitical uncertainties on commodity markets using a time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model. Our results indicate that the effects of geopolitical and financial uncertainties on commodity dynamics are concentrated in the short-term, and commodity volatility is more affected than returns. The volatility of commodity futures responds differently to different types of financial uncertainty shocks, and the uncertainty shocks caused by financial stress have produced relatively large effects, especially since the global financial crisis. Furthermore, our findings contradict traditional wisdom, as we observe that the uncertainty shocks caused by financial liquidity lead to increased commodity returns only in the short term. There are obvious heterogeneity responses of commodity futures in different sectors to uncertainty shocks. Energy and industrial metals are more affected than other commodities. Our findings are an important reference for decision makers and investors.

The Dynamic Correlation between China’s Policy Uncertainty and the Crude Oil Market: A Time-varying Analysis

ABSTRACT This research investigates the dynamic correlation between China’s policy uncertainty and the crude oil markets (i.e. domestic and international markets) using monthly time-series data from May 2003 to December 2018. To consider the non-linear and dynamic properties, we adopt the time-varying parameter structural vector autoregression model (TVP-SVAR) to estimate the dynamic correlations between the time series. By employing four categorical policy uncertainty indices, i.e. monetary policy uncertainty index (MYPU), fiscal policy uncertainty index (FLPU), exchange rate policy uncertainty index (EXER), and trade policy uncertainty index (TEPU), our results reveal that the correlation between China’s policy uncertainty and real crude oil returns is time-varying and non-linear. Specifically, the independence between policy uncertainty and oil returns varies more constantly and at a high degree while the time-varying interaction between policy uncertainty and global oil production (global economic activity) varies at a lower frequency and at a low level. Furthermore, regarding the associations between categorical policy uncertainty and global oil returns, the average correlation of EXER (negative) is the strongest one, followed by FLPU (negative), then MYPU (positive), and finally TEPU (negative). Moreover, it is noteworthy that WTI (Daqing) crude oil prices are utilized to increase the robustness of our conclusions. Finally, we generally confirm the dynamic and negative correlation between China’s geopolitical risk and crude oil returns. It is evidently clear from the results that investors should pay close attention to the policy uncertainty to avoid the adverse impact of specific policy uncertainty on crude oil returns.