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UID:event-9450@www.amse-aixmarseille.fr
DTSTAMP:20260422T113456Z
CREATED:20260422T113456Z
LAST-MODIFIED:20260422T113456Z
STATUS:CONFIRMED
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SUMMARY:phd seminar - Suzanna Khalifa*\, Mathias Silva Vazquez**
DTSTART:20221122T100000Z
DTEND:20221122T111500Z
DESCRIPTION:*This paper explores the relationship between female genital cu
 tting (FGC) and the marriage market. I develop a general equilibrium model 
 of parents' decisions to cut their daughters\, where the bride price\, the 
 groom’s traditional payment to the bride’s family upon marriage\, is de
 termined endogenously in the marriage market. The model predicts that in a 
 context where FGC is a marker of chastity\, an unobservable but valuable tr
 ait in the marriage market\, the practice increases the marital surplus\, t
 he bride price. I use a difference-in-differences approach and test the mod
 el’s predictions on Egyptian data. I build a village-level dataset of the
  coverage of an anti-FGC campaign\, using archive information on Egyptian r
 adio transmitters and Irregular Terrain Model (ITM) software. I find that c
 ohorts exposed to the campaign are 13% less likely to be cut and receive a 
 24% lower bride price. To further support my finding that FGC generates mar
 riage market returns\, I provide evidence suggesting that the scarcity of c
 ut women led to an increase in their bride price. When investigating whethe
 r FGC is a marker of chastity\, I find that the decline in FGC is substitut
 ed by an increase in pre-marital virginity testing and child marriage. Fina
 lly\, to better understand whether these marriage market returns provide an
  incentive for parents to cut their daughters\, I conduct a cross-Africa an
 alysis. I find that the practice of bride price is associated with a 16% hi
 gher likelihood of a daughter being cut.**The recent literature on income d
 istribution analysis has paid increasing attention to the biases arising fr
 om applying the usual models for income distributions to data suffering fro
 m reporting or non-response errors. In particular\, a large strain of this 
 literature focuses on dealing with these biases through performing correcti
 ons or imputations to the data prior to the analysis. Most of these correct
 ions\, however\, either rely on arbitrary choices for merging different dat
 a sources such as survey data and administrative tax records\, or lack a fo
 rmal ellicitation of the sources of biases they attempt to correct for. Thi
 s presentation proposes a parametric framework for integrating formally-def
 ined reporting and/or non-response processes to standard interpersonal inco
 me distribution models. By requiring an explicit income reporting function\
 , relating observed incomes in data to (potentially unobserved) true income
 s and to relevant individual characteristics\, the reporting or measurement
  errors considered to affect the data are given formal treatment. Secondly\
 , by requiring an explicit response probability function relating non-respo
 nse probabilities to individuals' characteristics and incomes\, the non-res
 ponse biases considered to affect the data are also integrated to the incom
 e distribution model. Analytical expressions for deriving probability densi
 ty functions (pdf)\, cumulative distribution functions (cdf)\, and Generali
 zed Lorenz curves (GLC) will be covered. As illustration\, the framework is
  applied to derive the pdf\, cdf\, and GLC of integrating to a Generalized 
 Beta distribution of the second kind (GB2) model for income distribution a 
 linear progressive under-reporting process on high-incomes and a truncation
  for missing top-incomes. This 'expanded' model is then taken to data on in
 comes from the European Union's Statistics on Income and Living Conditions 
 (EU-SILC) to yield distributional estimates integrating both types of corre
 ctions.\\n\\nContact: Camille Hainnaux: camille.hainnaux[at]univ-amu.frDani
 ela Horta Saenz: daniela.horta-saenz[at]univ-amu.frJade Ponsard: jade.ponsa
 rd[at]univ-amu.frNathan Vieira: nathan.vieira[at]univ-amu.fr\n\nPlus d'info
 rmations: https://www.amse-aixmarseille.fr/en/events/suzanna-khalifa-mathia
 s-silva-vazquez-0
LOCATION:MEGA
URL;VALUE=URI:https://www.amse-aixmarseille.fr/en/events/suzanna-khalifa-mathias-silva-vazquez-0
CONTACT:Camille Hainnaux: camille.hainnaux[at]univ-amu.frDaniela Horta Saen
 z: daniela.horta-saenz[at]univ-amu.frJade Ponsard: jade.ponsard[at]univ-amu
 .frNathan Vieira: nathan.vieira[at]univ-amu.fr
TRANSP:OPAQUE
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