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PRODID:-//AMSE//Event Calendar//FR
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UID:event-13073@amse-aixmarseille.fr
DTSTAMP:20260623T212950Z
CREATED:20260623T212950Z
LAST-MODIFIED:20260623T212950Z
STATUS:CONFIRMED
SEQUENCE:0
SUMMARY:phd seminar - Niccolo Rescia*\, Ivan Conjeaud**
DTSTART:20260630T090000Z
DTEND:20260630T103000Z
DESCRIPTION:*This paper examines how droughts and floods affect Kenya’s d
 omestic debt market between 2000 and 2024. Combining monthly issuance data 
 for Treasury bills and bonds with disaster and macro-fiscal records\, we es
 timate the dynamic effects of climate shocks on borrowing costs\, issuance\
 , and transmission channels. Droughts significantly raise long-term borrowi
 ng costs\; Treasury bond yields rise by about 200 basis points within seven
  to eight months\, while floods cause short-lived spikes in short-term rate
 s and liquidity tightening. Issuance volumes show no consistent adjustment\
 , suggesting that prices rather than quantities absorb climate stress. Fisc
 al responses appear muted\, indicating that financial rather than fiscal ch
 annels dominate. These findings imply that climate risks are already embedd
 ed in Kenya’s domestic financing conditions. As such shocks intensify\, d
 ebt managers should integrate climate risk into issuance strategies\, enhan
 ce transparency\, and strengthen liquidity support mechanisms.**We study a 
 model of algorithmic collusion in continuous time in which two firms use Q-
 learning algorithms to set prices in a Bertrand duopoly. The firms update t
 heir prices at times dictated by a Poisson clock. We introduce a simple par
 ameter controlling for the synchronicity of the firms' algorithms' updates\
 , ranging from perfect synchronicity like in previous models of algorithmic
  collusion\, to independence. Using extensive numerical experiments\, we sh
 ow that algorithmic collusion gradually disappears when the synchronicity b
 etween the algorithms' updates decreases\, and completely vanishes when the
 y update independently. Specifically\, we show that (i) the payoffs collect
 ed in the long run by the algorithms are no different than the ones collect
 ed by algorithms playing randomly (ii) the punishment-reward strategies gra
 dually appear when the level of synchronicity increases\, and are absent wh
 en the algorithms update independently. We show the last point by recording
  a large number of the algorithms' reactions to unilateral price cuts and c
 ompare them with the reactions of strategy-agnostic algorithms. Performing 
 a clustering task on these reactions reveals that for synchronous algorithm
 s\, the reactions to price cuts are very well distinguishable from that of 
 random algorithms\, while they are not distinguishable at all for algorithm
 s that update independently. These findings have important implications for
  algorithmic collusion.\\n\\nContact: Xavier Chatron-Colliet: xavier.chatro
 n-colliet[at]univ-amu.frArmand Rigotti: armand.rigotti[at]univ-amu.fr\n\nPl
 us d'informations: https://amse-aixmarseille.fr/en/events/niccolo-rescia-iv
 an-conjeaud
LOCATION:Îlot Bernard du Bois - Amphithéâtre\, AMU - AMSE\, 5-9 boulevar
 d Maurice Bourdet\, 13001 Marseille
URL;VALUE=URI:https://amse-aixmarseille.fr/en/events/niccolo-rescia-ivan-conjeaud
CONTACT:Xavier Chatron-Colliet: xavier.chatron-colliet[at]univ-amu.frArmand
  Rigotti: armand.rigotti[at]univ-amu.fr
TRANSP:OPAQUE
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