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This chapter contributes to the growing global VAR (GVAR) literature by showing how global and national shocks can be identified within a GVAR framework. The usefulness of the proposed approach is illustrated in an application to the analysis of the interactions between public debt and real output growth in a multicountry setting, and the results are compared to those obtained from standard single country VAR analysis. We find that on average (across countries) global shocks explain about one-third of the long-horizon forecast error variance of output growth, and about one-fifth of the long-run variance of the rate of change of debt-to-GDP. Evidence on the degree of cross-sectional dependence in these variables and their innovations are exploited to identify the global shocks, and priors are used to identify the national shocks within a Bayesian framework. It is found that posterior median debt elasticity with respect to output is much larger when the rise in output is due to a fiscal policy shock, as compared to when the rise in output is due to a positive technology shock. The cross-country average of the median debt elasticity is 1.45 when the rise in output is due to a fiscal expansion as compared to 0.76 when the rise in output follows from a favorable output shock.

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.

This paper presents an integrated overview of the empirical literature on the impact of all forms of unconventional monetary policy on macroeconomic variables and on markets.

This survey covers the findings concerning portfolio rebalancing, signaling, liquidity, bank lending and confidence channels.

The positive effect of QE announcements on stock and bond prices seems to be unified across studies. A contagion effect from US QE to other emerging markets is identified, while currency devaluation is present in most cases for the country that its central bank adopted such policies. Moreover, impacts of non-conventional practices on GDP, inflation and unemployment are examined. The studies presenting weak instead of strong positive effects on inflation are more, and these studies, also, present weak positive effects on GDP growth.

Based on the large body of research on non-conventional action taking, this is the first survey including effects of each country that adopted quantitative easing (QE) measures and that provides results from every methodology employed in order to estimate unconventional practices' impacts.

The purpose of this study is to explore the inherent instability, if any, in the context of investment in stocks of environment friendly companies (or the “green” stocks) across the globe using the time series momentum (TSM) trading strategies.

Using the monthly data for the Green Indexes from the USA, the Europe and the Asia-Pacific region over 2003-2019, the authors construct TSM trading strategies to examine the efficacy of regional Green Indexes as well as two diversified global green portfolios to offer abnormal return to attract investors, particularly speculators. The authors’ explore further whether such strategies could operate as hedging instrument. A comparison of results across different regions helps the authors establish a universal nature, if any, of investment in green stocks.

The study finds that regional Green Indexes are unable to outperform the market. The global green portfolios perform significantly better. The inefficacy of the relevant time series momentum trading strategies rules out the possibility of speculations. However, the number of profitable momentum strategies is significantly higher for the diversified portfolios in longer run. The portfolios perform significantly better in outperforming the buy-only strategies as well. The stable market, escalated demand and the resulting increment in valuation of green stocks make adoption of greener technologies a choice rather than a forced obligation. This offers a solution to the problem of Tragedy of Common.

Sustained increase in investment in green stocks is crucial from an environment perspective, as better valuation of their stocks would indubitably convince firms to reduce their carbon footprints. A continued enthusiasm however would require investors’ faith in it. Presence of momentum profit would invite speculators leading to irrational exuberance, dwindling confidence and consequent fragility. Literature on green investment is relatively sparse with the threat of its vulnerability issues left largely unnoticed. The authors’ study fills these gaps.

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact on the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between alternative oil market models, let alone the basis for the sometimes divergent conclusions reached in the literature. The purpose of this survey is to provide a guide to this literature. Our focus is on the econometric foundations of the analysis of oil market models with special attention to the identifying assumptions and methods of inference.

In seminal work, Den Haan et al. (2007, 2010, 2011) show business loans respond in the opposite direction of what may be intended by monetary policy action in the United States and Canada. Based on various approaches, identification schemes, and samples, we document evidence this loan puzzle is not exclusive to developed economies but is also pervasive in emerging markets. We find business loans generally decline following expansionary monetary policy shocks. A preponderance of statistical and structural evidence indicates important transmissions of this puzzle from the United States to emerging markets.

Purpose – This chapter aimed to investigate hedge funds market risk. One aims to go further the traditional measures of risk that underestimates it by introducing a more appropriate method to hedge funds. One demonstrates that daily hedge fund return distributions are asymmetric and leptokurtic. Furthermore, volatility clustering phenomenon and the existence of ARCH effects demonstrate that hedge funds volatility varies through time. These features suggest the modelisation of their volatility using symmetric (GARCH) and asymmetric (EGARCH and TGARCH) models used to evaluate a 1-day-ahead value at risk (VaR).

Methodology/Approach – The conditional variances were estimated under the assumption that residuals t follow the normal and the student law. The knowledge of the conditional variance was used to forecast 1-day-ahead VaR. The estimations are compared with the Gaussian, the student and the modified VaR. To sum up, 12 VaRs are computed; those based on standard deviation and computed with normal, student and cornish fisher quantile and those based on conditional volatility models (GARCH, TGARCH and EGARCH) computed with the same quantiles.

Findings – The results demonstrate that VaR models based on normal quantile underestimate risk while those based on student and cornish fisher quantiles seem to be more relevant measurements. GARCH-type VaRs are very sensitive to changes in the return process. Back-testing results show that the choice of the model used to forecast volatility has an importance. Indeed, the VaR based on standard deviation is not relevant to measure hedge funds risks as it fails the appropriate tests. On the opposite side, GARCH-, TGARCH- and EGARCH-type VaRs are accurate as they pass most of the time successfully the back-testing tests. But, the quantile used has a more significant impact on the relevance of the VaR models considered. GARCH-type VaR computed with the student and especially cornish fisher quantiles lead to better results, which is consistent with Monteiro (2004) and Pochon and Teïletche (2006).

Originality/Value of chapter – A large set of GARCH-type models are considered to estimate hedge funds volatility leading to numerous evaluation of VaRs. These estimations are very helpful. Indeed, public savings under institutional investors management then delegate to hedge funds are concerned. Therefore, an adequate risk management is required. Another contribution of this chapter is the use of daily data to measure all hedge fund strategies risks.

This paper aims to investigate the relationship between global economic fluctuations and human development through four transmission channels (foreign direct investment (FDI), official development aid (ODA), remittances and export earnings) in Egypt as an open developing economy, in the period 1990–2015.

The paper uses a vector autoregressive model, which implies examining the impulse response functions and variance decompositions.

The results indicate that human development is negatively affected by global economic fluctuations through the four channels, namely, ODA, FDI, export earnings and remittances. In addition, the most effective transmission channels are FDI in the short run and export earnings in the long run.

While a large body of literature addresses the direct impact of business cycles and economic shocks on human development, only some studies focus on the indirect impact. The contribution is to identify the indirect impact of global economic fluctuations on human development in a developing economy, considering four transmission channels and to determine the most important of these channels. Moreover, using the human development index is an addition in this paper as most previous literature depends on other human development indicators such as children’s health, employment and schooling.

The purpose of this paper to examine how global economic policy uncertainty (GEPU) affects export flows of emerging market economies.

This study examines the effect of GEPU on 28 emerging markets' export performance. GEPU variable used in the authors’ empirical analysis is measured by partial least square (PLS) factor loading model with the help of 24 countries' economic policy uncertainty index. A panel vector autoregression (VAR) model is employed for the estimations and monthly data over the 2006:01–2019:12 period are used.

The empirical findings show that while the real external income is the main factor that affects export flows, the real exchange rate is the least effective variable with regard to the variance decomposition, which is not expected by the related economic theory. Panel VAR estimations results confirm the previous studies and find that GEPU affects export flows negatively and significantly.

To the best of the authors’ knowledge, this is the sole study in terms of focusing on the impacts of GEPU on the export volume of emerging markets. The contribution of this paper is twofold. Firstly, a large set of countries with monthly frequented data that assist to capture uncertainties better is used. Secondly, the global economic policy index is obtained by employing the PLS method, which provides more robust results that are calculated with respect to the dependent variable.