Financial sector and economic growth amid external uncertainty shocks: Insights into emerging economies

Abstract

The study aims to shed new lights on the lead-lag relationships between the financial sector (RFSI) and economic growth (GDP) in the midst of global economic policy uncertainty (GEPU) shocks for BRICS economies. Hence, the bivariate, partial, and wavelet multiple correlations techniques are employed. From the bivariate analysis, we document positive bi-directional causality between the RFSI and economic growth over the sample period. The partial wavelet reveals that GEPU shocks distort the significance and directional comovements between the RFSI and GDP. Moreover, the outcome from the wavelet multiple cross correlations (WMCC) indicates that the RFSI is a first mover at most time scales for the BRICS economies. This is followed by GEPU which either leads or lags for most scales, especially for South Africa. The impact of GEPU on RFSI and GDP is worst for South Africa in about four cases in the medium-, and long-terms. This signifies that South Africa’s financial markets and economic growth are vulnerable to GEPU. However, the impetus for GEPU to drive the comovements between the financial sector and economic activity was less pronounced in the pre-COVID analysis conducted with the WMCC. The study supports both the supply-leading and demand-following hypotheses. Our findings also underscore the need for policymakers, investors and academics alike to incessantly observe the dynamics between finance and growth across time and periodicity while considering adverse shocks from global economic policy uncertainty in tandem.

Spillovers and contagion between BRIC and G7 markets: New evidence from time-frequency analysis

“…Recent developments in the global economy (e.g., the 2011/12 EDC, Brexit issues, US-China trade tension, COVID-19 pandemic, etc. ), coupled with the crises they come with, warrant both assessments and re-assessments of existing conclusions about market blocs, their extent of integration, portfolio diversification prospects, through appropriate methods that account for the heterogeneous, complex, and adaptable behaviours [ 26 ] of market participants. Therefore, the time-frequency spillovers, contagion, and pairwise interrelations between the BRIC index and its members, and between BRIC and G7 economies, were investigated in this study.…”

“…It is instructive to note that although the markets of BRIC and G7 are distinct in diverse phases, the recent growth in emerging markets and the new alliances formed between developing economies explicates their potential of becoming future developed markets [ 16 ] and this is not far from BRIC markets [ 4 ]. Notwithstanding, increasing growth and alliances, which result in the liberalisation of economies, increase the chance of economic and financial market integration [ 26 ], which could easily wipe off diversification advantages associated with assets from emerging markets. Invariably, capital flows and direct foreign investment in emerging markets may be impacted and could further translate into worsened stock market performance.…”

Flights‐to‐and‐from‐Quality with Islamic and Conventional Bonds in the COVID‐19 Pandemic Era: ICEEMDAN‐Based Transfer Entropy

“…We contribute to the scanty literature-that overcome these gaps-in a novel, unique, and more appropriate approach. We employ the entropy approach inspired by the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), a datadriven technique, to assess the flow of information between global equities and bonds from both Islamic and conventional markets, taking into consideration the complexities [5,17,18] in investor behaviour within Islamic and conventional markets. Investor complexities could be revealed through the application of decomposed time series so that they eliminate weak signals, leaving behind true signals only [19].…”

Vulnerability of Sustainable Islamic Stock Returns to Implied Market Volatilities: An Asymmetric Approach

“…Moreover, the robustness of these estimates would hinge on the application of the causality in mean at various quantiles. ese are presented to clearly divulge the heterogeneous [30] behaviour of markets and their participants across market conditions of stressed, normal, or boom [11,[31][32][33][34].…”