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UID:event-13138@amse-aixmarseille.fr
DTSTAMP:20260521T000542Z
CREATED:20260521T000542Z
LAST-MODIFIED:20260521T000542Z
STATUS:CONFIRMED
SEQUENCE:0
SUMMARY:phd seminar - Kossi Agbanda*\, Luca Cerasoli**
DTSTART:20260526T090000Z
DTEND:20260526T103000Z
DESCRIPTION:*We study debt sustainability and pollution mitigation in a two
 -country model with perfect capital mobility. Pollution abatement is financ
 ed through taxes or public bonds\, while households can invest in productiv
 e capital or public bonds. We show that when the interest rate is low\, the
  economy may converge to an equilibrium characterized by high capital accum
 ulation\, sustainable public debt\, and improved environmental quality. How
 ever\, depending on the initial levels of debt and capital\, the economy ma
 y be relegated to an Environmental - Poverty Trap. We then analyze the role
  of fiscal policy and find that taxes on production and income can promote 
 capital accumulation and environmental quality by expanding the tax base th
 at finances mitigation. In contrast\, higher public spending on abatement m
 ay crowd out productive investment and weaken debt sustainability. Fiscal i
 nstruments also affect the international distribution of public debt. Highe
 r income taxes in the home country tend to increase foreign public debt\, w
 hereas higher production taxes can reduce it under certain conditions and g
 enerate positive welfare effects. Overall\, the effectiveness of fiscal pol
 icy depends on the level of interest rates and on the extent to which house
 holds internalize pollution externalities.**Since the beginning of the twen
 ty first century\, copulas have been introduced in f inance\, becoming a po
 werful tool to disentangle complex and non linear depen dence structures be
 tween assets and other variables. Yet\, dependencies do not remain static o
 ver time\, rendering Static Copulas unreliable. This article explores a dat
 a-driven rolling window estimation (RWE) approach to model dynamic dependen
 ce between weather conditions in the USA\, and the wheat Future prices\, a 
 setting where meteorological shocks have direct financial implications. Usi
 ng principal component analysis to compress high dimensional weather data\,
  we are able to remain in the bivariate case for our Copulas\, which will l
 ater prove to have a negative impact in terms of information loss. The RWE 
 method is benchmarked against the gold standard in terms of dynamic copulas
 \, the [Patton(2006)] model for Elliptical and Archimedean copulas. Then\, 
 the accuracy of the forecasts of the [Patton(2006)] models is tested agains
 t a simple ARMA(1\,1) model. Then from this simplistic base\, we will deriv
 e some more sophisticated dependence benchmarks and forecasting methods\, n
 amely DCCGARCH and GAS as in [Engle(2002)] and [Creal et al.(2013)Creal\, K
 oopman\, and Lucas] on the depen dence side\, and EGARCH and Stochastic Vol
 atility models by [Nelson(1991)]\, [Jacquier et al.(1994)Jacquier\, Polson\
 , and Rossi]\, and [Taylor(1986)].\\n\\nContact: Xavier Chatron-Colliet : x
 avier.chatron-colliet[at]univ-amu.frArmand Rigotti : armand.rigotti[at]univ
 -amu.fr\n\nPlus d'informations: https://amse-aixmarseille.fr/fr/evenements/
 kossi-agbanda-luca-cerasoli
LOCATION:MEGA - Salle Carine Nourry\, 424\, Chemin du Viaduc\, 13080 Aix-en
 -Provence
URL;VALUE=URI:https://amse-aixmarseille.fr/fr/evenements/kossi-agbanda-luca-cerasoli
CONTACT:Xavier Chatron-Colliet : xavier.chatron-colliet[at]univ-amu.frArman
 d Rigotti : armand.rigotti[at]univ-amu.fr
TRANSP:OPAQUE
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