Global Vector Autoregressive Research Articles

The transmission of international shocks to CIS economies: A global VAR approach

This paper employs a Global Vector Auto Regressive (GVAR) model to study the evolution of the response of the Commonwealth of Independent States (CIS) to foreign output and oil price shocks. During an observation period of two decades, cross-country trade and financial linkages experience notable changes. We find CIS countries to be highly sensitive to global and regional shocks, with that sensitivity increasing after the global financial crisis. CIS countries show the strongest responses to output shocks originating in the US, Russia and within the region itself, but their sensitivity to euro area shocks also increases substantially. Despite growing trade relations with China, the responses of CIS countries to output shocks originating in China are still relatively moderate.

Forecasting mortality with international linkages: A global vector-autoregression approach

This paper proposes a Global Vector Autoregression (GVAR) mortality model to simultaneously model and forecast multi-population mortality dynamics. The proposed GVAR model decomposes the global regression model into population-wise local systems. Each local system consists of an intra-population autoregressive component and a small set of global factors, which contain systematic mortality information of all populations. Such a decomposition substantially reduces the extra estimation cost of including new populations compared to unconstrained VAR models, and makes the GVAR model an efficient tool for analyzing the joint mortality dynamics of a large group of populations. Further, under fairly general assumptions, the proposed GVAR model could generate coherent mortality projections between any two ages in any two populations. Using single-age mortality data of 15 low-mortality countries, we find that the global factors have substantial explanatory and forecasting power of mortality changes of individual populations, and the proposed GVAR model could produce satisfying mortality forecasts under various settings.

Обзор зарубежного опыта по оценке влияния качественных показателей на экономические процессы с использованием моделей векторной авторегрессии (Review of Foreign Experience in Assessing the Impact of Qualitative Indicators on Economic Processes Using Vector Autoregression Models)

Russian Abstract: В данной работе првощится анализ использование глобальной векторной авторегрессии в современной международной торговле, а также в мировой экономике в целом для оценки эффективности экономических явлений и процессов.English Abstract: This paper presents the possibilities of using global vector autoregression models, which are used in the following cases: when assessing intercountry interdependencies, when assessing the effectiveness of any reforms in the country and their impact on the economy as a whole or on its individual indicators. In addition, the presented models can be used to assess the impact on the economy of a specific country or group of countries of changes in prices for hydrocarbon energy resources. In modern realities, GVAR models are used to assess the impact of the coronavirus pandemic on the global economy in general, and on individual countries.

Macroeconomic Consequences of Covid-19 in a Small Open Economy: An Empirical Analysis of Nigeria

Nigeria is a small open economy with a high level of external dependency especially on the export of crude oil for foreign earnings and government revenue and import of consumables goods including pharmaceutical products. Currently, China and USA contribute more than 35% of Nigerian total import and in addition with Euro area constitute top export destinations of Nigerian crude oil. Studies in the past have investigated the vulnerability of Nigerian economy to external shocks, however, the emerging shocks from global economy due to COVID-19 seems unprecedented. Thus, it is imperative to preemptively examine the likely spillover effects of COVID-19 pandemic to a small open economy like Nigeria based on shocks to strategic trade partners. Given this background, this study investigates the macroeconomic consequences of COVID-19 in China, the Euro area and United States of America (USA) in Nigeria using Global Vector Autoregressive (GVAR) approach. This modelling approach provides an opportunity to analyze international macroeconomic transmission of shocks and spillovers between different countries. It also provides a framework to offer adequate tools to deal with the curse of dimensionality that may arise during the analysis. Macroeconomic variables such as exchange rate, economic growth, inflation rate, trade flows and consumers’ spending were employed from Nigeria and other COVID-19 infected partner countries to build the GVAR model. Similarly, variable such as oil price and world commodity price index served as global variables. These variables were introduced quarterly to obtain stable behavioural interactions. Subsequently, simulations were performed to capture economic reality of COVID-19 and policy reactions in COVID-19 infected partner countries. The study identified output and inflation shocks in USA and China as important external shocks to the Nigerian economy however, oil price shocks constitute the biggest external threat to the economy during and post COVID-19 era. © 2021 Penerbit Universiti Kebangsaan Malaysia. All rights reserved.

Variations in the Effects of a Single Monetary Policy: The Case of Russian Regions

This research analyses regional heterogeneity in the reaction of core inflation to shocks of a single monetary policy on the example of Russia. We use a global vector autoregression model to reveal impulse response functions of core inflation in Russian regions to monetary policy shocks. The average 5-year cumulative response of regional core inflation to a MIACR shock of 1 percentage point (pp) is ‒0.74 pp. For 77 out of 80 regions, the 5-year cumulative core inflation response is found to be statistically significant. If we exclude three statistically insignificant responses and discard the four regions with the highest and lowest responses, we get a spread of ‒0.55 to ‒0.93 pp with a standard deviation of 0.12. We show that, over a one-year horizon, the heterogeneous response to monetary policy shocks can moderately reduce the heterogeneity of the response of regional inflation to exchange rate shocks. However, the magnitude of this effect is limited. According to the analysis of the regional heterogeneity factors, the higher are the share of extractive industries in the gross regional product of a region, the share of loans to manufacturing sector, the share of loans to small enterprises, as well as the unemployment rate, the stronger will be the reaction of the core inflation to the monetary policy shock. The degree of heterogeneity in the Russian regions’ core inflation response to monetary policy shocks, the set of factors explaining this heterogeneity, and the explained variation in the regional response (30–40% depending on the model specification) turn out to be comparable to similar indicators in other countries with pronounced regional heterogeneity.

Assessing the impact of COVID-19 on global fossil fuel consumption and CO2 emissions

We assess the effect of the COVID-19 pandemic on global fossil fuel consumption and CO2 emissions over the two-year horizon 2020Q1-2021Q4. We apply a global vector autoregressive (GVAR) model, which captures complex spatial-temporal interdependencies across countries associated with the international propagation of economic impact due to the virus spread. The model makes use of a unique quarterly data set of coal, natural gas, and oil consumption, output, exchange rates and equity prices, including global fossil fuel prices for 32 major CO2 emitting countries spanning the period 1984Q1–2019Q4. We produce forecasts of coal, natural gas and oil consumption, conditional on GDP growth scenarios based on alternative IMF World Economic Outlook forecasts that were made before and after the outbreak. We also simulate the effect of a relative price change in fossil fuels, due to global scale carbon pricing, on consumption and output. Our results predict fossil fuel consumption and CO2 emissions to return to their pre-crisis levels, and even exceed them, within the two-year horizon despite the large reductions in the first quarter following the outbreak. Our forecasts anticipate more robust growth for emerging than for advanced economies. The model predicts recovery to the pre-crisis levels even if another wave of pandemic occurs within a year. Our counterfactual carbon pricing scenario indicates that an increase in coal prices is expected to have a smaller impact on GDP than on fossil fuel consumption. Thus, the COVID-19 pandemic would not provide countries with a strong reason to delay climate change mitigation efforts.

Global imbalances, external adjustment and propagated shocks: An African perspective from a global VAR model

This paper examines the impacts of external adjustment related to global imbalances on the external accounts (trade balance, current account and net foreign asset position) and real output in oil-exporting and frontier markets in Africa via the trade and financial (valuation) channels. To this end, we estimate two global vector autoregression (GVAR) models for 47 countries across different regions, over the period 1979Q2–2016Q4. We also consider the relative importance of global oil price shock and financial market volatility (proxied by the VIX index) as potential drivers of global imbalances. Our results show that the exchange rate policies in the US and China are equally important for economic activity and external accounts of African countries, with changes in China’s real effective exchange rate (REER) exerting greater influence on the external accounts of these developing countries. The effects of a positive oil shock and heightened financial market volatility are transmitted into African countries via both the trade and the financial channels, but the differentiated impacts of the oil price shock deepen the external imbalances between oil-exporters and frontier markets in Africa. The trade channel emerged as the main transmission mechanism for these external shocks, while the role of valuation effect working through changes in REER is limited, and negligible with respect to the oil price shock.

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 18 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.

COVID-19, Macroeconomic Dynamics and Fear in Europe: A Network Global VAR Approach

The COVID-19 pandemic has exerted severe impacts on the socioeconomic fabric of worldwide countries, spreading financial and economic instability, affecting sentiment of market participants and institutions, and causing an unprecedented epidemic-related economic crisis. Interconnectedness is a key determinant for the spread of a crisis in the network structure of entities, as large shocks tend to propagate to the economy in its complexity. In this paper we combine the statistical and econometric literature concerning generalized forecast error variance decomposition (GFEVD) with network science to study the topology of spillover indices across countries, macroeconomic variables and economic sentiment data. To this aim, we propose a dynamic network framework derived from a Global Vector Autoregressive model (GVAR), a suitable macroeconometric model to consider simultaneous multi-level interdependencies across variables, which we analyse through the lens of network theory. We apply our methodology to study the interrelated dynamics of a set of European countries' by looking at the Industrial Production, the Retail Trade and the Economic Sentiment indexes over the period 01/2000-03/2021. Our main results show how different crises exert diverse impacts on real economy, economic sentiment and on the entire countries' macroeconomic network structure. While the aggregate impact of the Global Financial Crisis on the network interrelationships in Europe is approximately the same in terms of global spillover magnitude as that induced by the COVID-19 outbreak, the latter seems to be more persistent over time, and with starkly diverse implications on the temporal network structure. We also demonstrate that, overall, economic sentiment tends to be an informationally dominant node in the network over real economic variables, even during the Global Financial Crisis period. However, the two components have recently swapped their roles due the COVID-19 outbreak, meaning that such a large, unexpected, and non-financial shock has allegedly caused the real economy to dominate macroeconomic expectations.

Measuring the Connectedness of the Global Economy

We develop a technique to exploit forecast error variance decompositions to evaluate the macroeconomic connectedness embedded in any multi-country macroeconomic model with an approximate vector autoregressive (VAR) representation. We apply our technique to a large global VAR model covering 25 countries and derive vivid representations of macroeconomic connectedness. We find that the US exerts a dominant influence in the global economy and that Brazil, China, and the Eurozone are also globally significant. Recursive analysis over the period of the global financial crisis shows that shocks to global equity markets are transmitted rapidly and forcefully to real trade flows and real GDP.

The Spillover Effect of Euribor on Southeastern European Economies: A Global VAR Approach

In this paper we employ a Global Vector Autoregressive Model (G-VAR) to examine macroeconomic and international monetary spillovers within the South Eastern European Countries over the period 2002–2016. In particular, we investigate how shocks in Euribor affect domestic interest rates, real effective exchange rates, foreign exchange reserves and the industrial production in six countries, namely Bulgaria, Croatia, Greece, North Macedonia, Romania and Slovenia, using monthly data. Our analysis shows that a negative Euribor shock has a positive effect, but of different size, on the industrial production across the countries. There is limited evidence regarding the effects of Euribor on foreign reserves, interest rates, and the real effective exchange rate. Our results provide significant implications and insights for authorities and policy makers.

CROSS‐SECTIONAL DEPENDENCE AND SPILLOVERS IN SPACE AND TIME: WHERE SPATIAL ECONOMETRICS AND GLOBAL VAR MODELS MEET

AbstractTo enhance the measurement of economic and financial spillovers, we bring together the spatial and global vector autoregressive (GVAR) classes of econometric models by providing a detailed methodological review where they meet in terms of structure, interpretation, and estimation. We discuss the structure of connectivity (weight) matrices used by these models and its implications for estimation. To anchor our work within the dynamic literature on spillovers, we define a general yet measurable concept of spillovers. We formalize it analytically through the indirect effects used in the spatial literature and impulse responses used in the GVAR literature. Finally, we propose a practical step‐by‐step approach for applied researchers who need to account for the existence and strength of cross‐sectional dependence in the data. This approach aims to support the selection of the appropriate modeling and estimation method and of choices that represent empirical spillovers in a clear and interpretable form.

Revisiting the effects of NAFTA

I use a global vector autoregression (GVAR) model with quarterly data since the inception of NAFTA (1994Q1–2016Q4) to investigate the effects of trade shocks to the USA and Mexico on major macroeconomic variables of Canada, Mexico and the USA. Structural generalized impulse response functions (SGIRF’s) are used to conduct the dynamic analysis and time varying trade weights are used to construct the foreign variables in each country model. The results show that the trade shocks have a significant positive impact in the region. A positive trade shock in the USA and Mexico increases output growth, wages, and equity prices and decreases unemployment rate in all the countries. However, inflation increases. The inclusion of China in the model dampens the positive effect of the USA and Mexican trade shock.

Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment

This paper examines the nexus between inflation and central bank interest rate policies in inflation-targeting countries. First, it looks at the role of inflation among other factors affecting monetary policy. Second, it looks at the drivers of inflation alone. Thereby, the role of international spillovers from other countries is explicitly regarded as well, with the aim of assessing the extent to which inflation is driven by other countries’ inflation or monetary policy is influenced by other economies. The empirical study covers advanced countries and emerging market economies for the period 1995 - 2016 and uses Bayesian global vector autoregression to model external linkages and to account for variable uncertainty. This study finds that inflation plays an important role for monetary policy. More importantly, central banks clearly consider additional factors and notably other countries’ key indicators when setting interest rates. Inflation in turn is determined by both internal and external factors like the exchange rate and other countries’ inflation. These findings are much more comprehensive than previous literature and demonstrate that central banks consider a multitude of domestic and global factors.

Country-level effects of the ECB's expanded asset purchase programme

ABSTRACT This paper evaluates the macroeconomic effects of the European Central Bank's (ECB) Expanded asset purchase programme (APP) on Latvia and other euro area jurisdictions and investigates the cross-border transmission mechanism. To that end, we employ two different vector autoregressive (VAR) models, namely a bilateral structural VAR with block exogeneity (BSVAR-BE) and a multi-country mixed cross-section global VAR with stochastic volatility (MCS-BGVAR-SV). We find that the APP had a limited and weakly significant impact on Latvia's output while the effect on inflation has been robust due to depreciation of the euro. Regarding other jurisdictions, results suggest that the ECB's asset purchases had a larger impact on industrial production in the countries where it drove down long-term interest rates the most via portfolio rebalancing channel. Despite that, our evidence suggests that the APP was mainly transmitted to inflation via exchange rate depreciation rather than through aggregate demand-driven shifts in the Phillips curve.

The Determinants of Indonesia’s Business Cycle

Abstract This study investigates the determinants of Indonesian’s business cycle using the global vector autoregressive (GVAR) approach, by including spillover responses within 33 countries with 2000 bootstrap replications. The results show that Indonesia’s business cycle is influenced by both domestic and external factors. In addition to exogenous shocks from output, the dominant domestic factors are monetary policy and price competitiveness. The dominant external factors are global economic activity and liquidity conditions, particularly those originating from the Chinese economy. Spillovers from a number of economies appear to shape Indonesia’s economic fluctuations. The paper discusses such relevant spillovers.

Housing market shocks in italy: A GVAR approach

In this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004−2016. In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the GVAR model is identified by using theory-driven sign restrictions. The spatio-temporal analysis carried through impulse response functions shows that there is evidence of a “ripple effect” mainly occurring through transaction volumes.

Macro Stress Testing Credit Risk: Case of Madagascar Banking Sector

Abstract This study proposes to assess the vulnerability of banking sector’s credit portfolio under macroeconomic shocks and to evaluate its impact on banking system capitalization. Our method uses the Global Vector Autoregressive (GVAR) Model to generate adverse macroeconomic scenarios. The GVAR model is combining by the satellite credit risk equation to find the non-performing loan under stress conditions. The advantage of using GVAR model is that on the one hand, it captures the transmission of global, external and domestic macroeconomic shocks on banks non-performing loans. On the other hand, this model considers the nonlinear pattern between business cycle and the bank credit risk indicator during the extreme events as highlighting by the macro stress test literature. The forecast of non-performing loan is then used to obtain stress projections for capital requirement for the banking system level. This article attempts to fill the lacks concerning the stress testing works about Madagascar which study is a recent framework, whose no study on dynamic macro stress testing was treated before. The Results outline the interaction of aggregate non-performing loan with macroeconomic evolution. The horizon of capital prediction shows that banking sector reacts most to a GDP shock. Also, Madagascar banking sector is quite resilient and remains sufficiently capitalized under all macroeconomic scenarios designed with a solvency ratio higher than the minimum regulatory CAR ratio.

The Impact of Domestic and Foreign Monetary Policy on Iran's economy: Global Modeling

One of the striking features of the business cycles is the patterns of co-movement of output, inflation, interest rates, and real equity prices across countries. This paper empirically examines the effects of domestic and foreign monetary policies on Iran's macroeconomic variables (including real production, inflation, short-term interest rate, and real exchange rate) using quarterly data over the 1996Q1-2015Q4 period and a global vector auto-regression model (GVAR) for Iran, the largest trading partners of Iran including China, India, Russia, South Korea, Turkey, the European Union, and the United State. The results of domestic monetary policies on Iran's macroeconomic variables illustrate a form of Price Puzzle on how monetary policy shocks affect inflation in Iran. The effects of the positive shocks of domestic interest rate on real GDP in Iran is negative. Iran's real exchange rate response to the positive shock of domestic interest rates is negative and significant. The results regarding the impact of the foreign monetary policies on Iran's macroeconomic variables illuminate that only the effects of a positive shock to China's interest rate are significant and negative on Iran's inflation. Besides, there is a significant independency of Iran's real GDP to the monetary policy shocks of the other trading partners of Iran. Also, the response of Iran's real exchange rate to positive monetary shocks in the EU and Turkey is at a positive and significant level. The results indicate that due to the closed economic structure of Iran, global economic crises that lead to a recession in other countries have had the least impact on the Iranian economy.

Modelling sectoral spillovers in the USA (1992–2015)

PurposeThis research paper uses a novel methodological approach to investigate the spillover effects among the key sectors of the US economy.Design/methodology/approachThe paper links the US sectors via a node theoretic scheme based on a general equilibrium framework, whereas it estimates the general equilibrium equation as a Global Vector Autoregressive process, taking into consideration the potential existence of dominant units.FindingsBased on our findings, the dominant sector in the US economy, for the period 1992–2015, is the sector of information technology, finance and communications, a fact that gives credence to the view that the US economy is a service-driven economy. In addition, the US economy seems to benefit by the increased labour mobility across knowledge-intensive sectors, thus avoiding the ‘employment trap’ which in turn enabled the US economy to overcome the financial crisis of 2007.Originality/valueFirstly, the paper models by means of a network approach which is based on a general equilibrium framework, the linkages between the US sectors while treating the sector of information, technology, communications and finance as dominant, as dictated by its degree of centrality in the network structure. Secondly, the paper offers a robustness analysis regarding both the existence and the identification of dominant sectors (nodes) in the US economy. Thirdly, the paper studies a wide period, namely 1992–2015, fully capturing the recent global recession, while acknowledging the impact of the global crisis through the introduction of the relevant exogenous dummy variables; Lastly and most importantly, it is the first study to apply the GVAR approach in a network general equilibrium framework at the sectoral level.