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DTSTART:20230326T010000
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DTSTART;TZID=Europe/Helsinki:20230119T103000
DTEND;TZID=Europe/Helsinki:20230119T113000
DTSTAMP:20260717T071810
CREATED:20230110T065840Z
LAST-MODIFIED:20230113T123136Z
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SUMMARY:Julia SCHAUMBURG   (Vrije Universiteit Amsterdam) "Joint modelling and estimation of global and local cross-sectional dependence in large panels"
DESCRIPTION:The Financial Econometrics Seminar: \nTime: 10:30 pm\nDate: 19th of January 2023\nRoom 3001 \nJulia SCHAUMBURG (Vrije Universiteit Amsterdam) “Joint modelling and estimation of global and local cross-sectional dependence in large panels” \nAbstract :We propose a new unified approach to identifying and estimating spatio-temporal dependence structures in large panels. The model accommodates global cross-sectional dependence due to global dynamic factors as well as local cross-sectional dependence\, which may arise from local network structures. Model selection\, filtering of the dynamic factors\, and estimation are carried out iteratively using a new algorithm that combines the Expectation-Maximization algorithm with proximal minimization\, allowing us to efficiently maximize an l1- and l2-penalized state space likelihood function. A Monte Carlo simulation study illustrates the good performance of the algorithm in terms of determining the presence and magnitude of common factors and local spillover effects. In an empirical application\, we investigate monthly US interest rate data on 12 maturities over almost 35 years. We find that besides a changing number of global dynamic factors\, there is evidence for heterogeneous local spillover effects among neighboring maturities. Taking this heterogeneity into account substantially improves out-of-sample forecasting performance. \nJoint work : Quint Wiersma (VU) and Siem Jan Koopman (VU) \nOrganizers:\n\nJean-Michel ZAKOIAN  (CREST) \nSponsors:\nCREST \n
URL:https://crest.science/event/julia-schaumburg-vrije-universiteit-amsterdam-joint-modelling-and-estimation-of-global-and-local-cross-sectional-dependence-in-large-panels/
CATEGORIES:Finance-Insurance,Financial Econometrics
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DTSTART;TZID=Europe/Helsinki:20230119T121500
DTEND;TZID=Europe/Helsinki:20230119T133000
DTSTAMP:20260717T071810
CREATED:20230106T055821Z
LAST-MODIFIED:20241104T085504Z
UID:14518-1674130500-1674135000@crest.science
SUMMARY:Zheng Wang (EUI Florence) "The linking effect: causal identification and estimation of the effect of peer relationship"
DESCRIPTION:The Econometrics Seminar:\nTime:12.15 – 13.30\nDate: 19th of January 2022\nRoom 3001 \nZheng Wang (EUI Florence) “The linking effect: causal identification and estimation of the effect of peer relationship” \nAbstract : The endogeneity of network formation has been a major obstacle to the study of peer influence. This paper proposes a causal identification solution in the potential outcome framework. Combining results from multiple causal inference and statistical network analysis\, I show that confounding can be addressed by inferring propensity scores of network link formation from the adjacency matrix. This identification strategy imposes minimum restrictions on the data-generating process and\, unlike existing econometric solutions\, does not rely on any parametric modelling. As an application\, I estimate the effect of high school friendships on bachelor’s degree attainment. While previous literature finds that exposure to more high-achieving boys makes girls less likely to obtain a bachelor’s degree\, I show that if the girls consider the boys as friends\, their interactions induce a positive impact instead. Since friendship endogeneity has been addressed\, the estimated effect is causal. \n  \nOrganizer:\nArne UHLENDORFF (CREST) \nSponsors:\nCREST \n
URL:https://crest.science/event/zheng-wang-eui-florence-the-linking-effect-causal-identification-and-estimation-of-the-effect-of-peer-relationship/
CATEGORIES:Economics,Seminars
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