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Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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MACRO-FINANCIAL RISK TRANSMISSION AND NET PORTFOLIO CAPITAL INFLOWS IN G7 ECONOMIES: EVIDENCE OF STATE-DEPENDENT DECOUPLING AND NONLINEAR RISK ANALYSIS

Authors: DAVID UMORU; FABIUS OSHIOTSE IMIMOLE; BEAUTY IGBINOVIA; OBOMEILE CYRIL; OSAYANDE MONDAY; SAHEED ALIU ALADEJANA;

MACRO-FINANCIAL RISK TRANSMISSION AND NET PORTFOLIO CAPITAL INFLOWS IN G7 ECONOMIES: EVIDENCE OF STATE-DEPENDENT DECOUPLING AND NONLINEAR RISK ANALYSIS

Abstract

Abstract The research examines how macro-financial risk factors interact with net portfolio capital inflows through dynamic nonlinear relationships across G7 countries during the period from 2010 to 2026 using state-dependent decoupling as its main theoretical foundation. The research refutes established confidence about risk and capital flow relationships through the application of three econometric methods, which include panel local projections for analyzing horizon-dependent system behavior and panel threshold autoregressive models for detecting regime-switching non-linearities and Copula-GARCH modeling for investigating tail-dependency behavior. The study demonstrates that investors mistakenly have confidence that portfolio flows maintain their independence from macro-financial risks because this relationship varies with different market regimes. Results indicate strong regime dependence. The period from 2010 until 2013, which featured extensive central bank monetary support allowed the G7 countries to achieve realistic economic decoupling. The period from 2020 to 2025 demonstrates flow behavior that includes two distinct patterns. Threshold autoregressive estimates enhance negative coefficients in high-risk states, and Copula-GARCH analysis suggests that deeper lower-tail dependence is experienced when states enter stress episodes, which means that, seemingly, mean-decoupling may be masked in a crisis co-movement. The estimations identify critical threshold namely a 118.4% debt-to-GDP ratio and a 0.82 standardized FX volatility benchmark, beyond which economies transition from resilient, decoupled regimes to fragile, coupled ones. Fiscal deterioration is significantly negative in 2015 to 2019 period. The study shows that liquidity risk and FX volatility maintain their influence to drive capital retrenchment and outflow whereas fiscal stance and government debt operate through threshold-activated coupling. Interest- rate differentials pull inflows between 2010 and 2013, weaken between 2015 and 2019, and in 2020 and 2026 first initiate outflows but eventually delayed yield-seeking inflows emerge. The findings demonstrate that G7 financial integration now experiences an efficiency-resilience trade-off which results in greater difficulties during synchronous tail-risks. We propose a new risk assessment method that establishes stability thresholds, which will require financial systems to implement safety standards that depend on market volatility, while permanent central bank swap lines will function as lower-tail dependency reducers. The research advances knowledge about portfolio investment flow patterns, which demonstrates the need for regime-based models to evaluate financial stability and risk assessment in G7 countries. JEL Classification: E44, F32, F36, F41, G11, G15, G18, C22, C33.

Keywords

Net Portfolio Investment Flows, Liquidity Risk, Fiscal Policy, Government Debt, Interest Rate Differentials, Foreign Exchange Volatility, Copula-GARCH, Panel Local Projection, Panel Threshold Autoregressive Model, G7 Economies, State-dependent Decoupling.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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