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VERSION:2.0
PRODID:-//AMSE//Event Calendar//FR
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UID:event-12043@amse-aixmarseille.fr
DTSTAMP:20260430T164213Z
CREATED:20260430T164213Z
LAST-MODIFIED:20260430T164213Z
STATUS:CONFIRMED
SEQUENCE:0
SUMMARY:phd seminar - Aurélien Espic*\, Maha Ouali**
DTSTART:20250624T090000Z
DTEND:20250624T103000Z
DESCRIPTION:*Commercial Real Estate (CRE) is a broad asset class covering a
 ll properties used by firms. If firms can directly own such properties\, th
 ey can also rent them from CRE investors. In this paper\, I show that takin
 g into account CRE investors enables to better understand the macroeconomic
  effects of credit supply shocks. I show empirically that CRE investors cap
 ture a large portion of firms' value added\, are particularly leveraged\, a
 nd rely heavily on debt to finance their investment. Based on these stylize
 d facts\, I then introduce CRE investors in a standard dynamic stochastic g
 eneral equilibrium model. In this model\, I show that credit supply shocks 
 have stark heterogeneous effects between CRE investors and other non-financ
 ial firms\, and lead to misallocation.**The growing need for energy flexibi
 lity has led to demand-response programs aimed at reducing peak electricity
  usage. EDF R&D has implemented several initiatives using smart meter data 
 from Linky devices. However\, evaluating their effectiveness remains challe
 nging due to individual consumption variability\, self-selection bias\, and
  limitations of standard causal inference methods. We simulate a controlled
  setting to highlight these issues and compare traditional approaches with 
 machine learning techniques such as SyncTwin\, which generates synthetic co
 ntrol units to handle unobserved confounders. Our results show that standar
 d methods often fail when time series complexity and hidden variables affec
 t treatment assignment\, underscoring the need for more robust causal infer
 ence models in energy policy evaluation.\\n\\nContact: Philippine Escudié:
  philippine.escudie[at]univ-amu.frLucie Giorgi: lucie.giorgi[at]univ-amu.
 frKla Kouadio: kla.kouadio[at]univ-amu.frLola Soubeyrand: lola.soubeyrand[
 at]univ-amu.fr\n\nPlus d'informations: https://amse-aixmarseille.fr/en/even
 ts/aur%C3%A9lien-espic-maha-ouali-0
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/aur%C3%A9lien-espic-maha-ouali-0
CONTACT:Philippine Escudié:&nbsp\;philippine.escudie[at]univ-amu.frLucie G
 iorgi:&nbsp\;lucie.giorgi[at]univ-amu.frKla Kouadio: kla.kouadio[at]univ-am
 u.frLola Soubeyrand:&nbsp\;lola.soubeyrand[at]univ-amu.fr
TRANSP:OPAQUE
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