Global Vector Autoregressive Research Articles

Assessment of the Effects of Monetary Policy Shocks from ECOWAS Member Countries to Nigeria

The paper evaluated the effects of monetary policy shocks from ECOWAS Member Countries to Nigeria using a combination of quarterly, annual time-series and panel data spanning from 1995–2021. The Standard Global Vector-Autoregressive (GVAR) Model of analysis was used to draw structural inference for the study using data on: consumer prices, international commodity prices (oil, agricultural raw material and metal ore), exchange rate, interest rate (short and long run), real output, money supply, and export diversification index. The result of the Impulse Response Function (IRF) revealed that shocks resulting from monetary policy transmission from the ECOWAS member Countries to Nigeria has diverse effects on Nigeria and is largely determined by the extent of monetary policy accommodative stance. The shock that may occur is likely to be country-specific because ECOWAS is an economic union that hardly has the foundation to share common economic or monetary risk. Additionally, the extent of trade flow between Nigeria and the rest of ECOWAS, determines the tendency that such shocks affect Nigeria. Finally, whether ECOWAS is a shock source, or a channel of transmission determines how much of an impact shocks from that region will have.

A network GVAR model for analyzing maritime transport demand: evidence from freight relationships among Greek ports

The aim of this study is to analyze the freight relationships between three major mainland Greek ports (Piraeus, Thessaloniki and Volos), based on containers’ transportation. The methodology used is the Global Vector Autoregressive (GVAR) model. The empirical analysis is based on time series data spanning the period January 1998–December 2012. The most important finding is that a shock in one port doesn’t have, in general, a significant impact on any other port and the corresponding effects settle down relatively quickly, usually in less than two months.

Technology Shocks and the Efficiency of Equity Markets in the Developed and Emerging Economies: A Global VAR Approach

We tested the connection between technology shocks and the efficiency of equity markets in developed and emerging economies. We augmented the Global Vector Autoregressive (GVAR) database that covers data on 33 developed and emerging markets with the newly constructed data for technology shocks involving two variants, one with 164 countries (GTS-164), and the other, which is more region-specific. covering only Organization for Economic Co-operation and Development (OECD) countries (GTS-OECD). Our analysis was then modeled with GVAR methodology. We found that a one standard positive innovation shock to global technology (GTS-164) raises real equity prices in nearly 70% of the markets considered, and this is sustained over the forecast periods. However, the response of real equity prices to a global-specific technology shock (GTS-OECD) is rather different. While this shock resulted in the immediate rise in real equity prices, it is only transient and dissipated after the third quarter of the forecast horizon in about 85% of these markets. By implication, the efficiency of the real equity market was assured for the region-specific technology shock rather than for the more encompassing measurement that takes account of numerous markets, not minding whether these markets are developed or emerging. In sum, technological shocks seem to have greater impacts on the efficiency of developed (including Euro) markets than other markets.

Estimation of Russia's GDP Losses Due to Sanctions Using the Global Vector Autoregression Model

Using mathematical and statistical methods, the authors made an attempt to estimate the losses in the domestic economy under the impact of the imposed sanctions. As a measurement tool is proposed a global vector autoregression model. In this model, the dynamics of GDP is considered as the main performance characteristic, and the rate of change in foreign trade turnover with key partners is used as the key prerequisites for the forecast. The use of this model building scheme is explained by the fact that the economic sanctions imposed on Russia have a negative impact on domestic macroeconomic indicators, and this happens through a variety of channels, key ones being the restriction of external demand and supply, leading to a decrease in trade turnover with the main trading partners, and change in oil revenues. This approach takes into account the relationship between the economies of different countries and their dependence on global markets. To obtain quantitative estimates, conditional forecasts are used as part of scenario analysis.According to the authors’ approach the losses from economic sanctions are measured by the decrease in the volume of Russia's foreign trade with key foreign trade partners, as well as by the discount for Russian oil compared to its global price. In addition to the forecast estimates, the validity of the approach is proofed with the forecast for the crisis period of 2014–2015 as an example. Based on the analysis of the current situation in foreign trade, Russian GDP in 2022 in the baseline scenario may fall by 5.4%, but with some reorientation of trade a decrease may be around 3.7%.

An analysis of the impact of China's macroeconomic performance on its trade partners: Evidence based on the GVAR model.

Economic strategies and planning are critical to a country's growth and development. China, like many other countries, is seeking the most cost-effective trade deals. Using the Global Vector Auto Regression (GVAR) model, this study examined the impact of a shock to China's macroeconomic factors on trading economies. The major findings reveal that there is no co-movement between the shock in Chinese gross domestic product (GDP) and German macroeconomic indicators; however, the shock has a positive and substantial influence on Japan's GDP and Unites States (US)' exchange rate. It is also worth noting that a shock to Chinese trade volume is more susceptible and more disturbing than a shock to US trade volume since it reduces trade volume and causes the Ren Min Bi (RMB) to devalue permanently. Furthermore, the analysis shows that Chinese stock prices have a major influence on German economy since China's GDP, trade volume, and currency appreciate over time when its stock price rises. Finally, the exchange rate shock is beneficial to Germany as it boosts GDP and trade volume but has a negative influence on US stock prices. The current study is, therefore, expected to be a suitable beginning point for the governments and policymakers of trading partners to design an effective trade policy to minimize the impact on major economic variables.

Gold and the global financial cycle

<abstract> <p>We examine the potential of gold and other precious metals as safe havens during negative market shocks caused by the Global Financial Cycle (GFCy). We analyze a vast global vector autoregressive (GVAR) model that includes developing and emerging market countries for a total of 33 countries, from 1979:Q2 to 2019:Q4. This approach allows us to account for individual country peculiarities while also considering the transmission of global shocks. We found that during financial market distress caused by a negative GFCy shock, gold, silver and platinum all serve as hedges. Interestingly, our results suggest that silver and platinum are better hedges than gold, offering greater positive returns in response to negative GFCy shocks, especially in recent years. Overall, our findings support the benefits of investing in precious metals, as they can help investors mitigate losses resulting from global financial shocks. While the metals vary in their hedging ability, platinum and silver offer even greater protection than gold.</p> </abstract>

Построение модели GVAR для российской экономики

The relationship between the economies of various countries and their dependence on the world markets indicate that for econometric analysis of the impact of external shocks on a particular economy, it is necessary to use a model of the global economy. The aim of this paper is to build a global vector autoregression model (GVAR), including Russia as one of the regions, and to obtain the impact of some external economic shocks on Russian macroeconomic indicators. We build a model that includes 41 of the world's major economies, including Russia, and the oil market. The special features of our model are structural shifts in the dynamics of Russian output and the new specification of oil supply and oil demand. Impulse response functions are used to obtain quantitative estimates. In this paper, we analyze the reaction of outputs, oil production volumes and oil prices in response to the output shocks of China and the United States. In response to the negative shock of output in the world's leading economies, outputs in the rest of the world declined for at least the first year after the shock. There was also a significant decline in oil prices and no significant change in oil production volumes in most countries. In addition, as part of the conditional forecast, we estimated the impact of the decline in global demand due to the Covid-19 pandemic on the Russian GDP as 1,3% drop. The rest of the de cline in Russian GDP can be attributed to the internal effects of the pandemic (lockdown). We also obtained a scenario forecast of the dynamics of Russian GDP depending on a decrease in trade and Russian oil price discount, within which the fall in Russian output could reach 3.3% in 2022.

Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers

We propose an approach for jointly measuring global macroeconomic uncertainty and bilateral spillovers of uncertainty between countries using a global vector autoregressive (GVAR) model. Over the period 2000Q1–2020Q4, our global index is able to summarize a variety of uncertainty measures, such as financial-market volatility, economic-policy uncertainty, survey-forecast-based measures and econometric measures of macroeconomic uncertainty, showing major peaks during both the global financial crisis and the COVID-19 pandemic. Global spillover effects are quantified through a novel GVAR-based decomposition of country-level uncertainty into the contributions from all countries in the global model. We show that this approach produces estimates of uncertainty spillovers which are strongly related to the structure of the global economy.

Cross‐country linkages between ASEAN and non‐ASEAN‐RCEP member states: A global VAR analysis

AbstractThe complex global value chains underlying the Regional Comprehensive Economic Partnership (RCEP) raise an important question on the macroeconomic (output, inflation, exchange rate, and interest rate) exposure of ASEAN to output shocks in the non‐ASEAN‐RCEP members, within the context of expanded regional architecture. This paper uses quarterly data from 1995 to 2018 to estimate a global vector autoregressive (GVAR) model, specially constructed for the RCEP. The GVAR model disentangles the effects and spillovers from output shocks originating in the non‐ASEAN‐RCEP through various trade channels – direct and indirect, and total exports and foreign value‐added (FVA). The model also quantifies the impact of global (the price of oil and materials) shocks on ASEAN through trade linkages. The output shocks in the non‐ASEAN‐RCEP have persistent effects on output growth in ASEAN when transmitted through the intermediary FVA channel than the export channel. The FVA channel is also important for propagating global shocks in the form of oil and material prices. The findings confirm that output in ASEAN is also highly exposed to output shocks originating in the non‐ASEAN‐RCEP economies. The FVA trade channel is vital for explaining the spillovers from the regional output shocks and global price shocks.

Modelling CESEE Countries Export Dynamics: Global Vector Autoregressive Approach

Abstract One of the main aspects of the transition process in Central, Eastern and Southeastern European (CESEE) countries was the trade liberalisation. As their financial systems are still underdeveloped and the trade channel is the dominant shock transmitter, this paper focuses on export dynamics for a selected set of CESEE countries. The employed methodology, Global Vector Autoregressive (GVAR) approach, allows modelling interactions and spillovers among countries. Furthermore, it enables joint modelling of exports and imports. This is of particular importance as the opening of new markets enabled astonishing export growth, but also opened the CESEE markets to foreign products. The empirical analysis reveals that a shock in German imports has a larger impact on CESEE countries’ exports than a shock in German output. Moreover, the results indicate that the role of the real exchange rate is less pronounced in comparison to previous similar research.

Agricultural Grain Markets in the COVID-19 Crisis, Insights from a GVAR Model

The objective of this paper is to combine cross-commodity and spatial price transmission analysis to study the dynamics of the global cereal feed market during the COVID-19 pandemic. After reviewing the nascent literature on the impact of COVID-19 on agricultural markets, we discuss the different impact channels on prices. Then, we provide stylized market reactions of three relevant feed markets, wheat, barley, and maize, to a set of simulated possible future shocks on oil prices, stock-to-use ratios, and export restrictions. These three shocks are useful to assess what could be the consequences of policy responses to COVID-19 (export restrictions) or the disruptions due to the virus (stock-to-use reductions), in a context of lower oil prices. To generate these market reactions, we use a Global Vector Auto Regression (GVAR) model where each market is modelled independently, and connected through trade-based composite variables. We expand the work on the global wheat market by introducing maize and barley. The results of the empirical analysis indicate that the fall in the oil price may have contributed to the stability of the world grain market in early 2020, despite fears of supply chain disruption. We also note that export restrictions could significantly increase global prices, and that such restrictions could affect more than the targeted commodity, through significant cross-commodity price linkages.

Oil Price Uncertainty Shocks and Global Equity Markets: Evidence from a GVAR Model

This paper examines the propagation of oil price uncertainty shocks to real equity prices using a large-scale Global Vector Autoregressive (GVAR) model of 26 advanced and emerging stock markets. The GVAR framework allows us to capture the transmission of local and global shocks, while simultaneously accounting for individual-country peculiarities. Utilising a recently developed model-free, robust estimate of oil price uncertainty, we document a statistically significant and negative effect of uncertainty shocks emanating from oil prices on the large majority of global stock markets, with the adverse effect of oil price uncertainty shocks found to be stronger for emerging economies as well as net oil-exporting nations. Interestingly, however, global stock markets exhibit a great deal of heterogeneity in their recovery following oil uncertainty shocks as some experience rapid corrections in stock valuations while others suffer from extended slumps. While the results are sensitive to the oil uncertainty measure utilised, they suggest that country diversification in the face of rising oil market uncertainty can still be beneficial for global investors as global stock markets exhibit a rather heterogeneous pattern in their recovery rates against oil market shocks.

The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model

Recent studies show that El Niño episodes are generally inflationary because they tend to increase the prices of agricultural commodities and crude oil. Given this, in this paper we examine the inflation-hedging property of gold (along with silver) from a novel perspective by analysing the impact of a negative shock to the negative component of Southern Oscillation Index (SOI) anomalies, i.e., El Niño shock. To this end, we apply a large-scale global vector autoregressive (GVAR) model to 33 countries covering both developed and emerging markets using quarterly data from 1980:Q2 to 2019:Q4. The GVAR methodology provides an appropriate framework to capture the transmission of global climate-related shocks while simultaneously accounting for individual country peculiarities. The results show that both gold and silver serve as good hedges in periods of inflation and rare disaster risks resulting from El Niño negative shocks. Interestingly, silver is a better hedge than gold, as implied by bigger positive real returns in response to El Niño shock. At the same time, La Niña shocks, captured by a positive effect to the positive component of SOI anomalies, fail to have a statistically significant impact on either gold or silver real returns. Overall, our results confirm the inflation-hedging benefits offered by the two precious metals, suggesting that investors can offset losses resulting from inflation-related risks stemming from El Niño events by investing not only in gold, but more so in silver.

Environmental risk of Covid-19 recovery

During Covid-19 pandemic world economy experienced negative growth rate, therefore energy consumption and consequently emission pollution decreased. According to Environmental Kuznets Curve, it is expected that energy consumption and emission pollution increase in response to Covid-19 economic recovery, even higher than its pre-pandemic level. The goal of this paper is to study the environmental risk of Covid-19 economic recovery. We use an Environmentally-Augmented Global Vector Autoregressive Model (E-GVAR) to trace dynamic effects of Covid-19 economic recovery on pollution emission. Using generalized impulse response functions (GIRFs), we investigated the effect of positive economic shocks in real per capita income in China and USA economies on total equivalent emission pollution. The results show that positive economic recovery affects emission pollution significantly. China and emerging economies may experience high risk while Europe region is moderately affected by this positive shock. A positive Economic Shock in China decrease pollution emission in USA over time. It can be attributed to substitution effect of Chinese product in global market. Generally, our results demonstrate spillover effect of transition shocks from large economies to the rest of world and highlights the importance of linkages in the world economy.

Small open economies and external shocks: an application of Bayesian global vector autoregression model.

This study assesses the impact of external shocks on select small open economies (SOEs) using the Bayesian variant of the global vector autoregression model with time varying parameters and stochastic volatility. We account for the curse of dimensionality in the multi-country VAR system by implementing three different priors in the estimation of the parameters of the model: the Minnesota (M-N) prior of Doan–Litterman et al. (1984; Litterman 1986); the Normal-Gamma (N-G) prior of Park and Casella (Bayesian Anal 1:515–533, 2008); and the Stochastic Search Variable Selection (SSVS) prior of George and McCulloch (1995) as extended by Koop and Korobilis (2010, 2013). From our simulation results, we found that global economies of the USA, Western Europe and China are the major drivers of cyclical fluctuation in the SOEs. However, in spite of the perceived superior influence of China on the SOEs GDPs’ response to external shocks, we found no evidence to conclude that the influence is significantly greater than those exerted by the United States or Europe on the bloc’s economies.

Modelling Determinants of Inflation in CESEE Countries: Global Vector Autoregressive Approach

Abstract After a prolonged period of relatively stable price levels, the beginning of the third decade of the 21st century has brought inflation once again into the spotlight. This paper focuses on the inflation dynamics in a set of post-communist countries that eventually became members of the European Union. Due to EU accession augmented by the globalization process and involvement in global value chains (GVC), the international impacts are becoming progressively important for the domestic inflation dynamics and domestic variables are not sufficient to fully describe the domestic inflation dynamics. The employed methodology, Global Vector Autoregressive (GVAR) approach, allows modelling interactions and spillovers among countries, making the most of its advantages over the usual VAR models that model each economy separately and panel models, where countries are often treated as independent units. The results of the empirical analysis confirm that the globalisation process has led to increasing the importance of international impacts on the domestic inflation dynamics. On the other hand, the results also indicate that accounting for a larger set of countries decreases the severity of the commodity price shocks and makes them less persistent. Furthermore, monetary policy acts as a buffer against adverse shocks, especially in the countries that are still not members of the euro-zone. The findings of the paper show that the analysed countries are pronouncedly heterogeneous. Hence, each of the analysed economies has its own set of country-specific factors which, from country to country, play a more important or a less significant role in explaining national inflation dynamics. Thus, the paper should contribute to a more comprehensive understanding of the inflation dynamics in the policy-making context.

Unintended Transnational Effects of Sanctions: A Global Vector Autoregression Simulation

ABSTRACT The debate on unintended consequences of sanctions, such as their adverse effects on human rights, public health, or the economy beyond intended sectors in the target state, has become increasingly popular over the last couple of decades. Interestingly, however, this debate has mostly overlooked the transnational aspects of these unintended consequences. This study examines one such aspect, namely the economic spillover of sanctions to neighboring countries. Our global vector autoregression oil and inventory model (GOVAR) simulations on Indonesia, a medium-level oil producer, indicate sanctions may spill over to its neighbors’ domestic economy. The risk and nature of spillover varies with respect to the type of sanctions employed, timing of sanctions, and the macroeconomic indicator in the neighboring state in question. Equity markets appear especially susceptible to a contagion effect. Understanding how a sanction spills over to neighboring states can help sender states design sanctions that minimize regional disruptions.

Risky mortgages, credit shocks and cross-border spillovers

This paper describes a novel methodology of measuring risky and conservative mortgage credit using household survey data for 17 European Union countries and the United Kingdom. In addition, we construct time series for both types of credit and embed them into a global vector autoregressive (GVAR) model, so as to study how shocks to both variables affect domestic output and propagate across countries through cross-border banking exposures. The results show that a decrease in risky credit can have long-lasting positive effects on GDP, both in the originating country and its most exposed peers, while a fall in conservative credit is detrimental. In some geographies, negative shocks to both types of credit reduce output, a feature linked to the lower relevance of homeownership which implies that mortgage credit plays a less prominent role in the domestic economy.

How does the EU's COVID-19 economic recession impact the renewable energy of other countries? The spillover effect

This work is aimed to explore the indirect impact of the EU's COVID-19 economic recession on global renewable energy consumption from the perspective of spillover effect. To this end, a global vector autoregressive (GVAR)-energy model was constructed based on the data of 33 major economies. After unit root test, cointegration test, weak exogeneity and structural stability test, the simulation results show that the spillover effects of the EU economic recession do not lead to a decline in the renewable energy consumption in all other countries. In fact, the spillover effect of the EU economic recession leads to an increase in renewable energy consumption in a small number of other countries, such as India. However, the spillover effect of the EU economic recession leads to a decline in renewable energy consumption in most other countries in the long run. Especially, the spillover effect of a 1% decline in the EU economy causes renewable energy consumption in the United States and China to fall by approximately 0.1% and 0.8%, respectively. Targeted renewable energy development policies should be developed to reduce the negative spillover effects of EU COVID-19 economic recession on renewable energy development.

Market Integration and Price Dynamics under Market Shocks in European Union Internal and External Cheese Export Markets.

The dairy sector in the European Union (EU) has experienced policy changes and market shocks recently. Using the global vector autoregressive (GVAR) model, this paper explores regional market integration, the feedback between market shocks and price dynamics, and the link between EU’s cheese export markets and energy market. This paper assesses and compares which influencing factors are typically associated with intra-EU and extra-EU cheese export price movement with regards to shocks to crude oil price, farm-gate raw milk price, and consumer price index (CPI) for food and cheese production of six representative EU member states, respectively. Using generalized impulse response functions, this paper finds that EU’s internal cheese export market is not well integrated, while EU’s external market is well integrated, with France as an exception. It also finds that the external cheese export market is vulnerable to shocks from the energy market compared to the internal market. Raw milk prices from the upstream supply chain have strong spill-over effects on EU’s internal cheese export market, yet their impact on extra-EU cheese export prices is relatively less significant. The movement patterns of extra-EU cheese export prices of Ireland and the UK show similar patterns in the long run. It is concluded that the dynamics of cheese export prices in the internal and external markets of the EU are different under market shocks.