Time-varying Parameter VAR Model 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.

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.

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.

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.

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.

Energy market reforms in China and the time-varying connectedness of domestic and international markets

China is the world's largest energy consumer and a considerable force in international energy markets. Continuous market reforms in the country together with the ongoing energy transition due to the commitment to carbon neutrality have brought fundamental changes to Chinese energy markets and have resulted in new sources of uncertainty in international energy markets. It is therefore important to investigate market linkages between China and the world from a dynamic perspective. This paper adopts the time-varying parameter VAR (TVP-VAR) model and the network spillover approach to explore the time-varying linkages between China and the international energy markets. The results show that the marketization process in China has led to significant changes in spillover patterns between international energy markets and Chinese domestic markets. Dynamics in the Chinese energy markets have played an increasingly important role in affecting international energy price movements. There is also clear evidence that the energy transition process in China has driven risk spillovers from the country to the international energy markets.

Does vaccination help to reduce financial stress on tourism subsectors?

Although there is rapid vaccination progress in the US and improvement in broad service activity upon reopening, no meaningful recovery has been achieved in tourism-related sectors until now. Therefore, we take a deep dive into tourism-related sectors and investigate how the effect of COVID-19 vaccination progress differentiates on the financial distress of tourism subsectors. Using a time-varying parameter VAR model, we quantify the financial distress in each tourism subsector and relate these measures with a daily number of newly vaccinated people. Our empirical findings indicate that specific tourism subsectors respond more to vaccination progress, and accordingly, financial stress has started to decline in these sectors. However, the effects of vaccination on airlines and hotel sectors are insignificant, implying that the recovery process will take longer in these subsectors.

Examination Of The Nonlinear Relationship Between, Exchange Rate, Oil Prices and the Food Prıces in Turkey: Time-Varying Parameter VAR (TVP-VAR) Models

Bu çalışmada, 2006:1-2021:12 döneminde Türkiye’de reel döviz kuru ve ortalama reel petrol fiyatları ile gıda enflasyonu arasındaki zamanla değişen dinamik ilişkiler incelenmiştir. Bu amaçla TVP-VAR modellerinden yararlanılmıştır. Çalışmadan elde edilen bulgular, reel döviz kurunun gıda enflasyonu üzerindeki etkisinin COVID-19 döneminde artış gösterdiğini ve döviz kurunda Ekim 2021 tarihinden itibaren yaşanan dalgalanmaların gıda enflasyonu üzerindeki etkisinin en yüksek seviyeye ulaştığını ortaya koymuştur. Ayrıca, 2021 yılında başlanan aşılanma sürecinin üretim ve talep artışına yol açmasıyla birlikte, ortalama reel petrol fiyatlarında yaşanan artışların gıda enflasyonunu önemli ölçüde yükselttiği tespit edilmiştir.

How do financial and commodity markets volatility react to real economic activity?

This paper examines the relationship between real economic activity and the financial and commodity markets using two approaches. First, we use the Discrete Wavelet Method to investigate the lead-lag dependence between real economic activity and these markets. Second, we use the Time-Varying Parameter VAR (TVP-VAR) model with stochastic volatility to examine the short- and long-term level of integration among these variables. Our wavelet results show that although the real economic activity shock lead co-movement with the chosen markets, it was led by these markets during periods of economic downturn as evidenced during the COVID-19 pandemic. Regarding the TVP-VAR results, we find that the connectedness between economic activity and the chosen markets is stronger during economic downturns or in the long run.

Total and Net-Directional Connectedness of Cryptocurrencies During the Pre- and Post-COVID-19 Pandemic

This paper presents how volatility propagates through the cryptocurrency market. Our paper provides evidence for volatility connectedness on cryptocurrencies. The different econometric techniques, including the stochastic volatility (SVOL) model and time-varying parameter VAR models using a quasi-Bayesian local likelihood (QBLL), are applied to measure the volatility of the cryptocurrency market. Using high-frequency, intra-day data of the largest cryptocurrencies over 2018–2021, we detect the great volatility of the cryptocurrency market are the beginning of 2019, the beginning of 2020, and throughout the year of 2021. The total connectedness values suggest that the cryptocurrency market becomes volatile as the new strains of the COVID-19 appear at the end of 2021. However, by using directional connectedness, we reveal that there are negative and positive spillovers from a specific cryptocurrency to other cryptocurrencies. The great fluctuations in the period before the COVID-19 health crisis stem from the positive resonance (symmetric) between the volatility of each cryptocurrency, while this health crisis leads to substantially positive and negative spillovers (asymmetric) of cryptocurrencies, and this makes market volatility weaker than it actually is.

Do Commodities React More to Time-Varying Rare Disaster Risk? A Comparison of Commodity and Financial Assets

Using a rare disaster risk database from almost the last one hundred years, we examine the differences in the reaction of asset prices to rare disaster risk between commodity and financial assets. We first employ time-varying parameter VAR (TVP-VAR) models to investigate the role of rare disaster risk in the price dynamics of major asset markets. The results indicate that disaster risk generally has a more intense and persistent impact on crude oil and stock markets when compared to gold and bond markets. However, the role of rare disaster risk differs substantially between commodity and financial assets, as well as between the short and long term. Moreover, when using a nonparametric causality-in-quantiles method to detect causal relationships, we provide evidence of the nonlinear causality effect of rare disaster risks on asset volatilities, and not their returns, except for crude oil. In addition, we demonstrate that augmenting a diversified portfolio of stock or bonds with gold can significantly increase its risk-adjusted performance. The findings have important implications for investors as well as policymakers.

Green markets integration in different time scales: A regional analysis

This paper examines the interactions among regional green energy equity markets and their dependence and connectedness with both uncertainties and price fluctuations in the global financial and crude oil markets. Using wavelets and spillovers based on a Time-Varying Parameter VAR model with stochastic volatility, we investigate the lead-lag relationships, co-movement and time-varying integration among these markets across different time domains. First, we found low covariance but positive and strong correlations among regional green energy equities across all time scales. Correlations are mainly negative and weak between regional green energy returns and uncertainties, except for Asia that exhibits positive correlation with oil price shocks in the long term. In terms of fluctuations in prices, results are similar regarding the covariance and correlations with global equity market prices but different for crude oil prices, where all regional green equity markets exhibit positive covariance and correlation with oil price changes especially in the medium term. Second, strong dependence exist among regional green energy equity markets in the medium and long term, especially between the U.S. and European markets. Similarly, dependence among green energy equities and global equity and oil markets both in terms of uncertainties and price fluctuations is weak in the short-run but strengthens towards the long-term except during the COVID-19 period when short-term integration rose sharply. Lastly, the global equity market is the leading source of risks while the Asian green equity market is the main net-receiver of shocks, especially in terms of price fluctuations in the global equity and crude oil markets. We document some crucial practical implications of these results both for investors and policy makers.

Bayesian Time-Varying Parameter VAR 모형을 이용한 아시아 주식시장과 경제정책 불확실성에 관한 연구

Bayesian Time-Varying Parameter VAR 모형을 이용한 아시아 주식시장과 경제정책 불확실성에 관한 연구

Dynamic interactions between oil price and exchange rate

This paper contributes to better understand the dynamic interactions between effective exchange rate (EER) and oil price for an oil-importing country like the U.S. by considering a Time-Varying Parameter VAR model with the use of monthly data from 1974:01 to 2019:07. Our findings show a depreciation after an oil price shock in the short-run for any period of time, although the pattern of long-run responses of U.S. EER is diverse across time periods, with an appreciation being observed before the mid-2000s and after the mid-2010s, and a depreciation between both periods. This diversity of response should lead policy makers to react differently in order to counteract such shocks. Furthermore, the reaction of oil price to an appreciation of U.S. EER is negative and different over time, which may generate different adverse effects on investment. The knowledge of such effects may help financial investors to diversify their investments in order to optimize the risk-return profile of their portfolios.