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The authors investigate the impact of the US stock market on the economies of the BRICS and major industrialized economies (G7).

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. Global vector autoregressive (GVAR) empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The authors summarize the results in four points: (1) financial integration variables increase the effect of the US stock market on the BRICS and G7, (2) the US shock produces similar responses in these groups regarding industrial production, stock markets and confidence but different responses regarding domestic currencies: in the BRICS, the authors detect appreciation of the currencies, while in the G7, the authors find depreciation, (3) G7 stock markets and policy rates are more sensitive to the US shock than the BRICS and (4) the estimates point out to heterogeneities such as the importance of industrial production to the transmission shock in Japan and China, the exchange rate to India, Japan and the UK, the interest rates to the Eurozone and the UK and confidence to Brazil, South Africa and Canada.

The results reinforce the importance of taking into account different levels of economic development.

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. GVAR empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

This article analyzes the impact of monetary policy on income inequality across 16 advanced economies. The author investigates three key points: (1) the relationship between domestic monetary policy and domestic income inequality, (2) the spillover effect of USA monetary policy (including quantitative easing) on international inequality and (3) the quantitative influence of the monetary policies of both the USA and the Eurozone on the formation of domestic income inequalities.

The author employed the Global Vector Autoregressive (GVAR) model, which uses Vector Autoregressive with Exogenous Variables (VARXs) models of each economy to build an integrated system that enables us to evaluate individual responses to global shocks.

The author's analysis reveals that (1) contractionary monetary policy exacerbates domestic inequality and (2) USA monetary policy, including quantitative easing, affects international inequality. Furthermore, the author's variance decomposition analysis highlights that USA monetary policy is especially influential on income inequality in Norway and Sweden. Additionally, the cointegrating analysis confirms that monetary policy's impact on inequality persists in the long term.

Most of the studies focused on investigating domestic economies as closed economies. However, the author's approach differs in that the author uses the GVAR, which treats all economies as open. This allows us to incorporate the world economy into the domestic dynamics and connect the economies using bilateral trade. Another advantage of the GVAR is that it captures spillover effects by modeling each economy and constructing the international economy.

In this work, the authors analyze the dynamic interdependencies between military expenditures and the real economy for the period 1970–2018, and the authors' approach allows for the existence of dominant economies in the system.

In this study, the authors employ a Network General Equilibrium GVAR (global vector autoregressive) model.

By accounting for the interconnection among the top twelve military spenders, the authors' findings show that China acts as a leader in the global military scene based on the respective centrality measures. Meanwhile, statistically significant deviations from equilibrium are observed in most of the economies' military expenses, when subjected to an unanticipated unit shock of other countries. Nonetheless, in the medium run, the shocks tend to die out and economies converge to an equilibrium position.

With the authors' methodology the authors are able to capture not only the effect of nearness on a country's military spending, as the past literature has documented, but also a country's defense and economic dependencies with other countries and how a unit's military expenses could shape the spending of the rest. Using state-to-the-art quantitative and econometric techniques, the authors provide robust and comprehensive analysis.

This paper aims to examine Nigeria’s dynamic output and output volatility connectedness with USA, China and India using quarterly data from 1981Q1 to 2019Q4.

The study adopted the network approach of Diebold and Yilmaz (2014) and used the normalized generalized forecast error variance decomposition from an underlying vector error correction model to build connectedness measures.

The findings show that the global financial crisis (GFC) increased the connectedness index far more than the 2016 Nigeria economic recession. The moderate effect of the 2016 Nigeria economic recession on the connectedness index underscores the fact that Nigeria is a small, open economy with minimal capacity to spread output shock. For both real output and its volatility, the total connectedness index rose smoothly and systematically through time, thereby leaving the economies more connected in the long run.

To the best of the authors’ knowledge, this paper is among the first to examine Nigeria’s dynamic output and output volatility connectedness with the USA, China and India using new empirical insights from the GFC versus 2016 Nigerian recession. The study, therefore, concludes that the Nigerian economy should be diversified immediately as a hedge against future real output shocks, while the USA, China and India should maintain and sustain their current policy frameworks to remain less vulnerable to real output shocks.

The study measures the total systemic risks and connectedness across commodities, stocks, exchange rates and bond markets in Africa during the Covid-19 pandemic.

The study uses the Diebold-Yilmaz spillover and connectedness measures in a generalized VAR framework. The author calculates the net transmitters or receivers of shocks between two assets and visualizes their strength using a network analysis tool.

The study found low systemic risks across all assets and countries. However, we found higher systemic risks in the forex market than in the stock and bond markets, and in South Africa than in other countries. The dynamic analysis found time-varying connectedness return shocks, which increased during the peak periods of the first and second waves of the pandemic. We found both gold and oil as net receivers of shocks. Overall, over half of all assets were net receivers, and others were net transmitters of return shocks. The network connectedness plot shows high net pairwise connectedness from Morocco to South Africa stock market.

The study has implications for policymakers to develop the capacities of local investors and markets to limit portfolio outflows during a crisis.

Previous studies have analyzed spillovers across asset classes in a single country or a single asset across countries. This paper contributes to the literature on network connectedness across assets and countries.

Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series. The initial history, published in 2012 for the 30th Anniversary Volume, describes key events in the history of the series and provides information about key authors and contributors to Advances in Econometrics. The authors update the original history and discuss significant changes that have occurred since 2012. These changes include the addition of five new Senior Co-Editors, seven new AIE Fellows, an expansion of the AIE conferences throughout the United States and abroad, and the increase in the number of citations for the series from 7,473 in 2012 to over 25,000 by 2022.

This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.

This study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.

The ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.

To the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.

This paper aims to explore the extreme effect of crude oil price fluctuations and its volatility on the economic growth of Middle East and North Africa (MENA) countries. It also investigates the asymmetric and dynamic relationship between oil price and economic growth. Further, a separate analysis for each MENA oil-export and oil-import countries is conducted. Furthermore, it studies to what extent the quality of institutions will change the effect of oil price fluctuations on economic growth.

As the effect of oil price fluctuations is not the same over different business cycles or oil price levels, the paper uses a panel quantile regression approach with other linear models such as fixed effects, random effects and panel generalized method of moments. The panel quantile methodology is an extension of traditional linear models and it has the advantage of exploring the relationship over the different quantiles of the whole distribution.

The paper can summarize results as following: changes in oil price and its volatility have an opposite effect for each oil-export and oil-import countries; for the former, changes in oil prices have a positive impact but the volatility a negative effect. While for the latter, changes in oil prices have a negative effect but volatility a positive effect. Further, the impact of oil price changes and their uncertainty are different across different quantiles. Furthermore, there is evidence about the asymmetric effect of the oil price changes on economic growth. Finally, accounting for institutional quality led to a reduction in the impact of oil price changes on economic growth.

The study concludes more detailed results on the impact of oil prices on gross domestic product growth. Thus, it can be used as a decision-support tool for policymakers.