Fiscal support and the impacts of tumbling oil prices from COVID-19 on MENA’s economy, energy consumption and environment

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.

The COVID-19 pandemic has caused a drop-in economic activity and energy consumption of the United States. This work aims to investigate the spillover effects of the United States’ COVID-19 economic recession on economic growth and energy consumption in other nations using a global vector autoregressive (GVAR) approach and quarterly data between 1990 and 2013 from 41 major countries/regions. On the one hand, the simulation results indicate that the US COVID-19 recession has a negative impact on other countries’ economic growth through trade ties, reducing the economic growth of other countries, especially for countries which have a close trade relationship with the US. In addition, the spillover effects of the US economic recession have different impacts on other countries’ energy consumption. Countries with the closest trade ties to the US are most affected, such as Japan and China. In addition, the impact of the US’ economic shock on energy consumption in developing countries is significant in the short term, while its impact on developed countries is significant in the long term. On the other hand, the simulation results of energy spillover effects indicate a reduction in US energy consumption slightly reduces economic growth in other nations. In addition, a reduction in energy consumption in the US does not have a significant negative impact on energy consumption in other developed countries. Furthermore, the spillover effect of declining energy consumption in the US on energy consumption in developing countries is significant in the short term. However, the spillover effects of falling energy consumption in the US on developing countries are different. The spillover effect of the decline in energy consumption in the US causes a slight decline in energy consumption in China and Brazil, whereas the spillover effect of the decline in energy consumption in the US does not cause a decline in energy consumption in India and Brazil.

China's Emergence in the World Economy and Business Cycles in Latin America Ambrogio Cesa-Bianchi (bio), M. Hashem Pesaran (bio), Alessandro Rebucci (bio), and TengTeng Xu (bio) As vividly illustrated by the impact of the recent global crisis on Latin America, the international business cycle is very important for the region's economic performance.1 The world economy, however, has undergone profound structural changes over the past two to three decades because of globalization and the emergence of China, India, and other large developing economies (including Mexico and Brazil in Latin America) as global economic players. As a result, the transmission mechanisms of the international business cycle to Latin America may have changed. This paper focuses on the emergence of China as a global force in the world economy and investigates how changes in trade patterns between China and the rest of the world may have affected the transmission of the international business cycle to Latin America. Specifically, we investigate empirically how shocks to gross domestic product (GDP) in China and the United States are transmitted to Latin America, conditional on alternative configurations of cross-country linkages in the world economy. We focus on China because its trade linkages with Latin America and the rest of the world have undergone the most dramatic shift over the period we consider. We focus on the United States because this country remains the largest trading partner of the Latin [End Page 1] American region as a whole and, historically, has been the major source of external shocks for Latin America. To complement this analysis, we also consider a GDP shock to the Latin American region itself and to emerging Asia (excluding China and India) because the analysis of these shocks helps shed light on the ongoing debate about the decoupling of emerging markets' business cycle from that of advanced economies. To conduct the empirical analysis, we use a variant of the global vector autoregressive (GVAR) model originally proposed by Pesaran, Schuermann, and Weiner and further developed by Dees and others.2 This is a relatively novel approach to global macroeconomic modeling that combines time series, panel data, and factor analysis techniques, which can be used to address a wide set of issues.3 In the first step of the methodology, each country is modeled individually as a small open economy by estimating country-specific vector error correction models in which domestic variables are related to both country-specific foreign variables and global variables that are common across all countries (such as the international price of oil). In the second step, a global model is constructed combining all the estimated country-specific models and linking them with a matrix of predetermined (that is, not estimated) cross-country linkages. Consistent with the existing GVAR literature and the main purpose of the application in this paper, we use trade shares to quantify the linkages among all the economies included in the GVAR model.4 The shocks that we investigate are not structural. However, given that our focus is on the transmission of GDP shocks across countries, the issue of identifying the sources of the shocks (whether they are due to demand, supply, productivity, or monetary policy) is not central to our analysis. The GVAR model that we use identifies the country-specific shocks by conditioning each variable on contemporaneous values of foreign-specific variables, which [End Page 2] renders the cross-country dependence of the shocks weak and of second-order importance. A novel, methodological contribution of this paper is to set up and estimate a GVAR model in which the country-specific foreign variables are constructed with time-varying trade weights, while the GVAR is solved with time-specific counterfactual trade weights. This allows us to study and compare the impact of GDP shocks with alternative configurations of cross-country linkages and to investigate how the transmission of shocks has changed since the emergence of China in the world economy. Specifically, we simulate GDP shocks in the GVAR model using trade weights at different points in time, thus capturing the fundamental aspect of China's rapidly changing role in the world economy: namely, its new pattern of trade linkages with Latin America and the...

The 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.

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

Inflation rate is considered undesirable in the modern globalized world due to its adverse and long-lasting impacts. The Kingdom of Saudi Arabia (KSA, hereafter) has also experienced inflationary pressure during the last few years, specifically post-COVID-19. However, the empirical literature on the determinants of inflation is indeed very scarce in the context of KSA. Amid this backdrop, this research paper aims to figure out the true determinants of inflation by focusing on the role of supply chain disruptions and global uncertainty by focusing on KSA. Quantitative data were collected from credible sources on a monthly basis for the period of 1998M01 to 2024M02 and were analyzed through the “Autoregressive Distributed Lag Model (ARDL)”. Our findings indicate that inflation in KSA is positively impacted by supply chain disruptions, global uncertainty, inflation spillovers from the United States, and money supply in the long run. Similarly, in the short run, only money supply, supply chain disruptions, and global uncertainty are responsible for the prevailing inflation rate in KSA. Moreover, the real effective exchange rate is positively and significantly linked with inflation only in the long run. Furthermore, positive shocks in oil prices cure inflation, while negative shocks in oil prices accelerate inflation in the short run. Our results are expected to shape policy formulation regarding the management of the inflation rate in KSA significantly.

The Determinants of Sovereign Bond Yield Spreads in the EMU: A GVAR Model

In this study, an attempt has been made to analyze and estimate the macroeconomic forecasting for Pakistan and its major twelve trading partners for the period of 1995Q1 to 2012Q4, using Global Vector Autoregressive (GVAR) Model. The key feature of GVAR model is to capture the independence and co-movement across countries. Secondly, it provides better forecasting performance. The GVAR model is estimated for twelve trading economies. During estimation, Pakistan economy is treated as single and domestic economy, whereas the other trading partners are treated as foreign economies. The important findings of this study are that the GVAR forecasts better than the VAR forecasts in most of the cases. Second, the foreign real GDP and foreign inflation rates are reflecting the significant impact of their domestic counterparts of Pakistan real GDP and inflation

This paper uses the global vector autoregressive (GVAR) modelling approach to study (1) the effects of negative output shocks on Bangladesh's following trading partners on Bangladesh's economy: the United States, China, Eurozone, India and Saudi Arabia (2) positive global oil price shocks. To represent Bangladesh's macroeconomics, the GVAR model contains four key macroeconomic variables as endogenous variables. They are (1) real gross domestic product (GDP), (2) real exchange rate, (3) short-term interest rates, and (4) inflation. The specified GVAR model is estimated using quarterly data from 32 countries/regions from 1993Q4 to 2016Q4. The findings of this paper are consistent with theoretical predictions that external shocks can and will be transmitted to an open economy operating under a fixed or managed floating exchange rate system. For example, quantitatively, if the real output of Bangladesh's trading partners' falls by 1%, its output will fall by 0.39%, while the inflation rate of Bangladesh's trading partners' rises by 1%, and Bangladesh's inflation rate will increase by 1.38%. Although the negative output shock of the US economy will not significantly affect the Bangladeshi economy, the negative output shock of the Chinese economy will have a negative and significant effect on the Bangladeshi economy. The negative output shock on the US economy has caused the real exchange rate of Bangladesh's currency to appreciate and raised its short-term interest rate, although it is not statistically significant. Contrarily, a negative output shock to China or other economies devalues the real exchange rate of the Bangladeshi currency, although it is not statistically significant. However, Bangladesh's interest rates have not responded to negative output shocks from its trading partners (except the United States and Saudi Arabia), and they are not statistically significant. One policy implication of Bangladesh's inflation being overly sensitive to external inflation shocks is that Bangladesh can and should make its currency exchange rate more flexible to protect its economy from external price shocks. Unexpectedly, the external oil price shock did not seem to have a significant impact on the Bangladeshi economy. One explanation is that the impact of foreign inflation on Bangladesh's economy may have reflected the impact of oil prices.

SUMMARYWe apply a global vector autoregressive (GVAR) model to the analysis of inflation, output growth and global imbalances among a group of 33 countries (26 regions). We account for structural instability by use of country‐specific intercept shifts, the timings of which are identified taking into account both statistical evidence and our knowledge of historic economic conditions and events. Using this model, we compute both central forecasts and scenario‐based probabilistic forecasts for a range of events of interest, including the sign and trajectory of the balance of trade, the achievement of a short‐term inflation target, and the incidence of recession and slow growth. The forecasting performance of the GVAR model in relation to the ongoing financial crisis is quite remarkable. It correctly identifies a pronounced and widespread economic contraction accompanied by a marked shift in the net trade balance of the Eurozone and Japan. Moreover, this promising out‐of‐sample forecasting performance is substantiated by a raft of statistical tests which indicate that the predictive accuracy of the GVAR model is broadly comparable to that of standard benchmark models over short horizons and superior over longer horizons. Hence we conclude that GVAR models may be a useful forecasting tool for institutions operating at both the national and supra‐national levels. Copyright © 2010 John Wiley & Sons, Ltd.

Inflation: The problems for aquaculture

The study examines the relationship between oil price shocks and selected macroeconomic variables in Nigeria. It adopts a Global Vector Autoregressive (GVAR) model, which includes Nigeria's major trade partners, in examining the relationship. This provides a holistic picture of how oil price shocks are conveyed to Nigeria via the first round as well as through the spillover effects. The variables employed are Real Gross Domestic Product (y), inflation (Dp), short-term interest rate (r), money supply (ms), and real effective exchange (epeps) as the domestic variables, while oil price is included as global variable. Quarterly data were used spanning the period 1979Q2 to 2013Q1. The economies included are Nigeria, the United States, Euro Area, India, China, Brazil, United Kingdom and South Africa. The findings of the study reveal that an upsurge in oil price leads to increase in real output, money supply as well as a mild increase in the real effective exchange rates of Nigeria while inflation and short-term interest rate fall.

Due to the dual shocks of the spread of the virus and lower oil prices, World Bank economists expect output of MENA to decline in 2020. This is in sharp contrast to the growth forecast of 2.6 percent published in October 2019. The growth downgrade of 3.7 percentage points is arguably a measure for the costs associated with the dual shocks of Covid-19 and the oil price collapse. These numbers are tentative. The true impact depends on future developments of the dual shocks, policy and society’s response, which depends on the transparent use of health and economic data. We recommend a two-step approach: It might be desirable to focus first on responding to the health emergency and the associated economic contraction. Fiscal consolidation and structural reforms associated with the persistent drop in oil prices and pre-existing challenges are also very important, but with proper external support, can wait until the health emergency subsides. Nevertheless, the MENA region has challenges that predate the crisis – it has been growing far slower than its peers. Had MENA’s growth of output per capita been the same as that of a typical peer economy over the past two decades, the region’s real output per capita would be at least 20% higher than what it is today. A large part of MENA’s low growth is arguably due to a lack of transparency. MENA is the only region that dropped in data transparency and capacity since 2005. We estimate that this has cost MENA 7-14 percent in GDP per capita losses since 2005. Lack of transparency hinders credible analyses of many important issues, two of which are highlighted in the report. First, lack of data transparency hampers credible analyses on the region’s debt sustainability – an important issue to examine after the crisis. MENA countries vary greatly in their debt reporting standards. World Bank economists and other external analysts do not have access to vital information about many types of public debt. Second, the unemployment and informality numbers in the region are debatable since MENA countries rely on varying definitions of employment with little harmonization across the region or with respect to international standards. This affects analyses of unemployment and informality.

Sustainability of Macroeconomic Policies, Inflation Targeting, and Crowding out