Time-varying Parameter VAR Research Articles

From oil surges to renewable shifts: Unveiling the dynamic impact of supply and demand shocks in global crude oil market on U.S. clean energy trends

Transitioning to renewable energies has become undeniably important in recent decades, especially for the United States. Oil price shocks are prominent determinants of renewable energy. Hence, this study examines the impacts of oil supply, aggregate demand, and oil-specific demand shocks on renewable energy consumption from 1973:01 to 2021:05 using Structural VAR and Time-Varying Parameter VAR models. Based on the results, oil supply shocks generally have a negligible effect on renewable energy, except those that originate from sharp changes in Saudi Arabian oil production and the U.S. recession-induced oil supply deficit. Aggregate demand shocks, such as those caused by the Persian Gulf War and the Asian financial crisis, negatively affect renewable energy by reducing investments and making oil more affordable. Conversely, oil-specific demand shocks, such as the 1979 Iranian Revolution and the 2008 financial crisis, initially reduce renewable energy attractiveness but ultimately lead to increased renewable energy consumption due to soaring oil prices. This study’s unique approach of separately examining global oil market shocks provides new insights, complementing and extending previous research on the relationship between oil prices and renewable energy consumption. Eventually, policy implications for strengthening incentive policies and adding punitive policies to seeking investment in renewable energy are proposed.

Dynamic analysis of the relationship between exchange rates and oil prices: a comparison between oil exporting and oil importing countries

Addressing the interconnectedness of oil prices and foreign exchange rates poses a substantial challenge and raises significant questions within economic research. Existing studies reveal a fragmented understanding of the dynamics between these crucial variables, highlighting a need for deeper investigation. This study extends previous research by employing the time-varying parameter VAR extended joint connectedness model and using the baseline approach called the generalized connectedness approach. Our research findings indicate that exchange rates and crude oil prices exhibit pairwise and total connectedness, varying over time. Furthermore, this connectedness experiences substantial increases during severe crisis periods. We uncover that exchange rates and crude oil prices not only share a dynamic, pairwise, and total connectedness but these results are stronger for oil exporting countries. However, these methods yield inconsistent results for various countries. Moreover, there is compelling evidence that fluctuations in exchange rates and oil prices can cause bi-directional and time-dependent shocks.

MONETARY POLICY UNCERTAINTY AND EXCHANGE RATE PASS-THROUGH: EVIDENCE FROM TURKEY

In this study, the impacts of monetary policy uncertainty (MPU) on second and third-stage ERPT in Turkey for the period June 2010–December 2023 are examined by using the Time-Varying Parameter VAR Model with Stochastic Volatility (TVP-VAR) developed by Nakajima (2011a, b). The findings of the study show that the time-varying ERPT coefficients increase in the first four periods after the MPU shock and then tend to decrease. The second-stage ERPT coefficients are greater than the third-stage ERPT coefficients over the whole period. The time-varying ERPT coefficients have increased rapidly since 2018. The second-stage ERPT coefficients respond to MPU shocks given at the dates when the CBRT Governors are dismissed before completing their terms of office by increasing more, while the third-stage ERPT coefficients respond by increasing permanently. Based on these findings, reducing monetary policy uncertainty by increasing the predictability of monetary policy decisions is recommended to reduce the ERPT.

Cross-category connectedness between Shanghai crude oil futures and Chinese stock markets related to the Belt and Road Initiative

This paper aims at investigating the cross-category time-varying frequency connectedness between Shanghai crude oil futures (INE), the CSI Belt and Road theme index, and seven Chinese stock markets affiliated with the Belt and Road Initiative (BRI), namely infrastructure, high-speed railway, green electricity, communication, ferrous metals, agriculture, and new energy markets. Using the novel time-varying parameter VAR (TVP-VAR) frequency connectedness model, we identify how the connectedness between INE and BRI-related stocks varies between the short-term, and long-term investment horizons. Our empirical findings reveal that the connectedness between INE and BRI-related stocks significantly increases during extreme market movements and mainly occurs at shorter time horizons. On the other hand, both INE and BRENT serve as net shock receivers, exhibiting relatively limited connectedness to BRI-related stocks. Notably, the correlation between INE and BRI-related stocks is significantly stronger compared to that observed with BRENT. We also observe that the INE exhibits a relatively strong correlation with infrastructure and ferrous metals compared to other stock markets, displaying a discernible bidirectional spillover effect. Our results document some practical enlightenment for investors and policymakers with various time horizons.

The asymmetric impact of oil market shocks on the time-varying connectedness and spillover of financial stress

ABSTRACT Applying a novel time-varying parameter VAR (TVP-VAR) extended joint connectedness approach this study first examines the connectedness and spillover of financial stress among twelve large Asian economies. The finding shows that the usually high connectedness of the financial stress among these economies was further elevated during the Asian financial crisis and global financial crisis but not significantly during COVID-19 pandemic. The direction of spillover depends on the level of economic development. Developed economies such as South Korea, Singapore and Hong Kong are significantly net transmitters of financial stress to other Asian economies whereas countries such as Pakistan and Indonesia are significantly net receivers. Applying linear and non-linear Markov-switching models this study further examines the impact of oil-supply, and consumption- and speculation-led oil-demand shocks on the dynamic connectedness of financial stress indexes. In the linear model only a speculation-led increase in demand for oil increases the connectedness. However, the Markov-switching model reveals that in the high-volatility regime all types of oil shocks influence the connectedness of the financial stress among these economies. This emphasizes the elevated role of oil market in transmitting financial stress across economies during the time of economic turmoil.

Crude oil futures prices and foreign exchange markets

ABSTRACTWe apply a time-varying parameter VAR (TVP-VAR) extended joint connectedness approach, in addition to the generalized connectedness approach, to understand the connectedness of crude oil futures price and exchange rates of major oil-dependent countries. We find time-varying nature of pair-wise and total connectedness that are usually elevated during events such as COVID-19, Brexit, European sovereign debt crisis and global financial crisis. Both joint and generalized connectedness approaches confirm that Japanese Yen and Russian Ruble are the leading net receiver of the shocks, though the two approaches provide mixed results for some other currencies. Moreover, there is strong evidence of time-varying and bi-directional shock transmissions between oil and foreign exchange markets. We also show that oil price volatility and gold price have predictive power on the connectedness. Lastly, we analyse the policy and portfolio implications.

Time-varying impact of supply chain pressures on US inflation

ABSTRACT We estimate a time-varying parameter VAR with stochastic volatility (TVP-VAR-SV) model using the global supply chain pressure index (GSCPI) to study the variation of the supply chain impact on US inflation over time. We find the increasing impact of the global supply chain shock on inflation, which has become more persistent during the COVID-19 pandemic. The findings suggest that supply chains have become a more influential in understanding economic variables, especially inflation.

How does climate policy uncertainty affect financial markets? Evidence from Europe

This study analyzes the time-varying effect of climate policy uncertainty (CPU) on the stock market and clean energy indices in the European context. For this purpose, we use the Bayesian time-varying parameter VAR model. The empirical results show that CPU shocks have a significant effect on the financial indexes. Returns on clean energy (crude oil) stocks increase (decrease) in response to heightened climate risk. Moreover, the COVID-19 pandemic is a relevant tipping point in CPU dynamics. These results offer important implications for European investors and policymakers in the context of the European climate-energy crisis.

Financial stress in Russia: Exploring the impact of oil market shocks

Oil market shocks significantly influence the financial and macroeconomic performance of resource-rich economies, serving as a critical anchor for their economic stability and growth. Russia is a significant exporter of oil and is geopolitically exposed; we examine the response of financial stress levels to decomposed oil market shocks, namely supply-side shocks, demand-side shocks, and financial risk exposures, during the period from July 13, 2012 to June 30, 2022, considering periods of historically abrupt oil price movements. We employ several econometric approaches to estimate our model, including the Cross-Quantilogram approach (CQ), Cross-spectral quantile coherency technique, and Time-varying parameter VAR model with stochastic volatility. Our findings reveal a robust intensification of financial stress in the Russian financial market when oil prices rise due to supply and demand shocks in the short term. Conversely, negative oil price shocks tend to diminish financial stress in the long run. Furthermore, our dynamic analysis indicates that the Russia-Ukraine conflict led to an increase in financial stress caused by oil market shocks, although the effect was comparatively weaker than during the US shale boom. Based on our research, we present several policy implications to address the identified challenges and promote financial stability in the face of oil market volatility.

Time varying connectedness between foreign exchange markets and crude oil futures prices

The relationship between crude oil futures and exchange rates has been the subject of several research studies. Through the utilization of a TVP-VAR (time-varying parameter VAR) extended joint connectedness methodology and the generalized connectedness technique to investigate the interconnectivity of oil futures prices of key oil-dependent nations and exchange rates, we contribute to the existing body of knowledge. Our findings indicate a time-varying nature of overall and pairwise connections, which typically intensifies during various periods such as the COVID-19 pandemic, Brexit, and the European sovereign debt crisis. The Japanese Yen and Russian Ruble appear as the primary recipients of net shocks, as suggested by both the generalized and joint connectedness methodologies. For other nations, similar methods yield conflicting results. Furthermore, there is clear evidence of time-dependent and bidirectional shock transmissions between the oil and foreign exchange markets. Our research provides valuable policy recommendations for stakeholders and diverse investors.

Impact of Geopolitical Risk on Financial Assets: Evidence from Time-Varying Parameter Var

Geopolitical events are expected to affect all countries, asset classes, and sectors. Vietnam is a large open economy, actively participating in a vast network of free trade agreements. Therefore, political conflicts in some regions will have both positive and negative impacts on the Vietnamese economy. Aiming to explore the dependency structure between the geopolitical risk index and stock market returns, this study has evaluated quite in-depth using the TVP-VAR method combining the wavelet coherence phase between February 2012 and April 2022. The results show that geopolitical risk has a heterogeneous effect on the return of financial assets, and the market does not respond to geopolitical tensions in a uniform manner. Our research uncovers new and interesting implications for policymakers and investors involved in the Vietnamese stock market.

Exploring the time-varying dependence between Bitcoin and the global stock market: Evidence from a TVP-VAR approach

This study examines the return dependence between Bitcoin and major international stock markets from January 1, 2018, to September 30, 2021. Utilizing a time-varying parameter VAR (TVP-VAR) model with stochastic volatility, we analyze the dynamics of the dependence structure while considering market uncertainty indices (UCRY Policy, UCRY Price and VIX) before and after the outbreak of COVID-19 pandemic. Our findings indicate that Bitcoin's role as a safe haven for stock markets has yet to be observed during the post-COVID-19 period. Furthermore, we observe varying impacts of the return correlation between different stock markets and Bitcoin, suggesting an asymmetric dependence. These results contribute to the ongoing discussion regarding Bitcoin's role as a safe haven asset and provide valuable insight for investors and policymakers.

Macroeconomic Effects of Fiscal Policy during the Covid-19 Crisis: Evidence from Bolivia at a Regional Level

This paper evaluates the impact of the fiscal policy applied in Bolivia during the Covid-19 crisis at a regional level. It includes two analyses: the economic slowdown at a regional level analyzed through a mixed frequency Bayesian var with a stochastic volatility model, and the impact and effectiveness of the fiscal policy using a time-varying parameter var model. The results indicate that the pandemic had a heterogeneous effect on the region’s economic activity and the capital expenditure from the national treasury was the most effective fiscal policy to reduce the recessive effects of the crisis. We also noted that some regions positively reacted to regional and local government capital expenditure.

Disentangling the geopolitical risk and its effects on commodities. Evidence from a panel of G8 countries

Geopolitical risk pertains to the potential impact of political, economic, and social factors on the global or regional landscape, giving rise to potential disruptions in the prevailing background. This paper examines the dynamic impact of country-specific geopolitical risk indexes on the G8 countries and commodity market prices. Using a sample of monthly data ranging from January 2001 to October 2022, after estimating a time-varying parameter VAR model, we perform an impulse response analysis that accounts for the major political and economic events that have shaken the past two decades. Our main findings show that geopolitical risk transmission differs from country to country and often depends on geographical proximity, that geopolitical risk appears to affect the energy sector more than metals and food, and that the effects of shocks tend to be absorbed within a year. We also find the magnitude of geopolitical shocks in the US and Russia to be the most relevant, especially after the 2008 global crisis and the Russia–Ukraine conflict in 2022. Our results could provide useful information to financial policymakers and market regulators to face external shocks, thereby achieving greater macroeconomic stability.

The effects of quantitative easing on Bitcoin prices

This study aimed to examine the impact of the US quantitative easing policy on Bitcoin Prices in 2017–2023. A Time-Varying Parameter VAR (TVP-VAR) model was constructed for discussing the price influence mechanisms of quantitative easing on Bitcoins. The study's empirical results showed that the impacts of quantitative easing policies on Bitcoin prices can vary over time, a temporary positive impact on Bitcoin prices through different channels was also observed. Furthermore, it was found to impose a long-term positive impact via the liquidity channel.

Analyzing the static and dynamic dependence among green investments, carbon markets, financial markets and commodity markets

PurposeThis paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020.Design/methodology/approachThis study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets.FindingsResults show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric.Practical implicationsThe findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios.Originality/valueThe study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.

The time-varying impact of foreign capital flows on house prices: evidence from South Africa

This study employs a time-varying parameter VAR with stochastic volatility (TVP-VAR) to investigate the time-varying impact of foreign capital flows on house prices in South Africa. The study also analyses the behaviour of the house price index using recursive unit root tests. The results of these tests show a statistically significant period of house price exuberance. The results of the TVP-VAR show a contemporaneous positive impact of foreign capital on house prices throughout the sample period, with the largest impact occurring during the period of house price exuberance. In addition, the international capital flows are found to aggravate the imbalances between demand and supply sides, thus enforcing the future house prices to comove with the housing supply.

Dynamic Volatility Spillover Effects and Portfolio Strategies among Crude Oil, Gold, and Chinese Electricity Companies

This paper examines the dynamic relationships and the volatility spillover effects among crude oil, gold, and Chinese electricity companies’ stock prices, from 2 December 2008 to 25 July 2022. By estimating the dynamic conditional correlation (DCC) model, we identify the time-varying correlation between crude oil, gold, and Chinese electricity stocks. Then, we use the time-varying parameter VAR model (TVP-VAR) to analyze the total and net volatility spillover effects. In addition, we compare the hedge ratio strategy and the portfolio weights strategy, as well as the corresponding hedging effectiveness among the crude oil, gold, and Chinese electricity companies. Considering the impact of the extreme events, we also extend the examination to the special period analysis of two crises, the Chinese stock market crash in 2015 and the COVID-19 pandemic in 2020. The results indicate that significant volatility spillover effects exist among crude oil, gold, and Chinese electricity companies’ stock volatility, and the total spillover effects show a sharp increase under the impact of the crisis. On average, gold is a much cheaper hedging tool than crude oil, whereas these two commodity assets remain net volatility receivers during the whole period and the crisis. However, it is worth noting that for specific assets, the impact of the crisis on spillover effects depends on the characteristics of crisis events and the assets analyzed. Additionally, most optimal weight strategies provide better hedging effectiveness than hedging strategies from the perspective of hedging effectiveness.

Time-varying effects of fuel prices on stock market returns during COVID-19 outbreak

This article explores the impact of fuel price movements on the stock market return of 2020 during the COVID-19 disruptions. In doing so, a monthly data of seven selected stock market indices representing developed and emerging economies globally was used for analysis. The study used a time-varying parameter VAR model to examine a time-varying causal association between oil prices and stock market returns and a novel quantile-causality approach to capture the fluctuations of these markets under COVID-19's varying market conditions. The study further utilises the entropy transfer approach to capture the Granger-causal relationship in the presence of nonlinearities of the data series. The results indicate a high information flow from fuel prices to the FTSE-100, Pacific, and European stock indicies, but not the other way round. The results show that, for the FTSE-100 and the European region, there is a two-way information flow between equities and natural gas, and vice-versa. However, a one-way information flow was established from the stock market to the Pacific and emerging economies.

Time-Varying Spillover of us Trade War on the Growth of Emerging Economies

In the wake of an unprecedented increase in the trade policy-related uncertainty of the US since 2017, we analyze the ability of a newspaper-based trade policy uncertainty index (TPU) of the US in predicting the growth rate of emerging market economies. The newspaper-based trade policy uncertainty index was developed by Caldara et al. (2020), while GDP data was obtained from the Global Economic Database maintained by the Federal Reserve Bank of Dallas, in the form of an aggregate value for all emerging economies. We analyze the data in a bi-variate VAR(2) setup, with the number of lags identified using Akaike Information Criterion, using the novel multivariate time-varying causality framework developed by Rossi and Wang (2019) on an effective sample of 1984:Q3 to 2019:Q3. Starting with the standard constant parameter Granger causality test, we find no evidence of TPU to the growth of GDP. We then proceed with the time-varying parameter causality test of Wang and Rossi (2019), where we find overwhelming evidence of the role of trade uncertainty in impacting the growth of emerging markets in a statistically significant manner, with the effect being on the rise since the Great Recession. Our results are robust to the usage of an alternative econometric methodology, metric of trade uncertainty, and also over an out-of-sample forecasting exercise. While the time-varying predictive analysis is the focus of our paper, causality tests are silent about the sign of the impact of TPU on the GDP growth of the emerging markets. Given this, we estimate a time-varying parameter VAR model with stochastic volatility (TVP-VARSV). We find that the impact is sharp and negative. Our results imply that policymakers in emerging countries must be aware of the possible threat of an upcoming recession in the wake of heightened trade policy uncertainty in the US, and hence, must be ready to undertake necessary (expansionary) policies to prevent a downturn in their respective domestic economies. To draw optimal policy responses, authorities would need to utilize time-varying econometric models, since the effect of uncertainty related to trade policies of the US are indeed non-constant over time.