Cet article analyse l'impact des financements intermédiés des institutions financières internationales sur le niveau d'informalité des économies africaines. En s'appuyant sur un panel de 39 pays africains couvrant la période 2000-2018, l'étude évalue dans quelle mesure ces financements, canalisés via des intermédiaires financiers locaux, constituent un levier de formalisation des activités économiques, en particulier des petites et moyennes entreprises. L'analyse mobilise une approche quasi-expérimentale combinant l'équilibrage entropique comme méthode principale et l'appariement par score de propension pour les tests de robustesse. Les résultats empiriques montrent que les financements intermédiés exercent un effet négatif et statistiquement significatif sur l'informalité, avec une réduction comprise entre 8 % et 13 % selon les spécifications. Ces résultats suggèrent que l'accès à des ressources longues et formalisées renforce l'inclusion financière, améliore la transparence et incite les entreprises à se conformer aux exigences institutionnelles. L'étude comble ainsi un vide dans la littérature en mettant en évidence le rôle spécifique des financements intermédiés comme instrument de soutien à la formalisation et au développement économique en Afrique.

Financial markets frequently exhibit dramatic episodes where asset prices undergo rapid growth followed by abrupt collapses, that are incompatible with standard linear time series models. While anticipative heavytailed linear processes offer a promising alternative for modeling such phenomena, they impose uniform bubble patterns across different episodes, contradicting empirical evidence. This paper introduces a new model, based on α-stable moving average aggregates, that accommodates heterogeneous bubble dynamics.

We establish the theoretical properties of this model, demonstrating that it admits a semi-norm representation on a unit cylinder, thereby enabling the prediction of extreme trajectories with varying growth dynamics. We develop a minimum distance estimation procedure based on the joint characteristic function and establish its asymptotic properties. Monte Carlo simulations confirm the estimator's good finite-sample performance across various specifications, and we implement a subsampling methodology to empirically verify the convergence to asymptotic normality. Our empirical application to the CBOE Crude Oil ETF Volatility Index successfully decomposes observed volatility dynamics into distinct components with different persistence properties, revealing that what appears as a single bubble episode actually consists of multiple superimposed processes with heterogeneous growth rates and crash probabilities.

Cross-border electricity trade in the Northeastern American grid helps U.S. markets mitigate structural deficits in low-carbon generation capacity. These deficits are partially offset by surplus exports from Québec (hydropower) and Ontario (nuclear generation). We use a Vine copula to assess the nonlinear interdependence of these markets.

Using hourly data from 2019-2023, we estimate the joint lower tail of regional net lowcarbon surpluses. In the unconditional distribution, the 5% Value-at-Risk (VaR) indicates an aggregate deficit of -1.3% of low-carbon generation. Regional VaR estimates reveal pronounced asymmetries as U.S. shortfalls exceed local low-carbon generation by about 130-178%. While Canadian regions are substantially less exposed in the lower tail. On heat-wave days, the aggregate deficit is -1.8% with the U.S. regional shortfalls about 200-250%. As heat waves increase in frequency and intensity, there will be an increase reliance on fossil fuels during electricity shortfalls.