ORCID Profile
0000-0002-9101-3362
Current Organisation
UNSW Sydney
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Wiley
Date: 02-09-2020
DOI: 10.1002/IJFE.2168
Abstract: Foreign portfolio investment (FPI) has been modelled with the aim of observing patterns, discovering potential inefficiencies and providing evidence for theories. Over the course of many studies, bilateral FPI appears to increase with an increase in the correlation between the gross domestic product growth rates of the sender and the receiver. The Capital Asset Pricing Model in financial theory predicts the opposite—and this is known as the correlation puzzle. One possible explanation is that the correlation is a proxy for both ersification benefits and informational asymmetry. Using seven cross‐sections of bilateral FPI holdings data from the CEPII Coordinated Portfolio Investment Survey for the years 2000–2006, we attempt to explain the correlation puzzle by augmenting the gravity model with random effects to account for heterogeneity in propensity to send and receive investments and with latent space position models to account for effects of unobserved country attributes, as well as transitivity, clustering, and balance in order to capture the information asymmetry and leave the correlation coefficient as a measure of the ersification benefit. We use maximum likelihood Heckman s le selection estimators to account for potential bias in estimators that can be caused by frequent zeros in our data, describing a model for the presence or absence of FPI between the two countries and a model for the level of FPI between two countries conditional on its presence. We find that if there is a presence of FPI between country s and country r , then as the correlation between the economic growth of these countries increases, the level of investment will decrease. However, this correlation has no significant impact on the decision of country s to invest in country r .
Publisher: Elsevier BV
Date: 03-2017
Publisher: Institute of Mathematical Statistics
Date: 03-2017
DOI: 10.1214/16-AOAS1010
Publisher: Institute of Mathematical Statistics
Date: 05-2015
DOI: 10.1214/15-STS517
Publisher: Oxford University Press (OUP)
Date: 20-03-2014
DOI: 10.1111/RSSB.12014
Abstract: Models of dynamic networks—networks that evolve over time—have manifold applications. We develop a discrete time generative model for social network evolution that inherits the richness and flexibility of the class of exponential family random-graph models. The model—a separable temporal exponential family random-graph model—facilitates separable modelling of the tie duration distributions and the structural dynamics of tie formation. We develop likelihood-based inference for the model and provide computational algorithms for maximum likelihood estimation. We illustrate the interpretability of the model in analysing a longitudinal network of friendship ties within a school.
Publisher: Elsevier BV
Date: 07-2011
Publisher: Foundation for Open Access Statistic
Date: 2023
Publisher: Springer Science and Business Media LLC
Date: 09-2020
Publisher: Institute of Mathematical Statistics
Date: 05-2015
DOI: 10.1214/14-STS502
Publisher: Informa UK Limited
Date: 10-2012
Publisher: Institute of Mathematical Statistics
Date: 11-2020
DOI: 10.1214/19-STS743
Publisher: Informa UK Limited
Date: 10-08-2023
Publisher: Oxford University Press (OUP)
Date: 12-10-2017
DOI: 10.1111/RSSC.12185
Abstract: Motivated by a real life problem of sharing social network data that contain sensitive personal information, we propose a novel approach to release and analyse synthetic graphs to protect privacy of in idual relationships captured by the social network while maintaining the validity of statistical results. A case-study using a version of the Enron e-mail corpus data set demonstrates the application and usefulness of the proposed techniques in solving the challenging problem of maintaining privacy and supporting open access to network data to ensure reproducibility of existing studies and discovering new scientific insights that can be obtained by analysing such data. We use a simple yet effective randomized response mechanism to generate synthetic networks under ε-edge differential privacy and then use likelihood-based inference for missing data and Markov chain Monte Carlo techniques to fit exponential family random-graph models to the generated synthetic networks.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 09-2021
DOI: 10.1097/IAE.0000000000003137
Abstract: To describe the novel observation of spontaneously migrating retinal cells from living donor surgical retinal explants that express progenitor cell markers in the absence of exogenous growth factors. Surgical retinal explants were harvested from 5 consecutive patients undergoing 23 G pars plana vitrectomy for the management of rhegmatogenous detachment. During surgery, equatorial flap tears were trimmed with the vitreous cutter and aspirated. Excised tissue was then regurgitated into a syringe containing balanced salt solution and immediately transferred to tissue culture. Migrating cells subsequently underwent immunohistochemical staining and their characteristics were compared with those of a spontaneously immortalized Müller stem cell line. Spontaneously migrating cells were observed from s les taken from all 5 patients from Day 2 to 10 after transfer to culture. These cells were found to express embryonic cell markers, including paired box 6 (Pax6), sex-determining region Y-box 2 (Sox-2), nestin, cone-rod homeobox, and cyclin-dependent kinase inhibitor 1B (p27 Kip1 ) as well as proteins consistent with early or retained differentiation down the Müller cell lineage, including glial fibrillary acidic protein and glutamine synthetase. After injury, the human equatorial retina is capable of spontaneously producing cells that demonstrate migration and that express progenitor cell markers. In addition, these cells express proteins consistent with Müller cell lineage. These initial observations support the assertion that the human retina may possess the potential for regeneration and that surgical retinal explants could also act as a ready source of retinal progenitor cells.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 07-2009
Publisher: Elsevier BV
Date: 05-2022
Publisher: Institute of Mathematical Statistics
Date: 2012
DOI: 10.1214/12-EJS696
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer International Publishing
Date: 2018
Publisher: SAGE Publications
Date: 06-07-2017
Abstract: Rank-order relational data, in which each actor ranks other actors according to some criterion, often arise from sociometric measurements of judgment or preference. The authors propose a general framework for representing such data, define a class of exponential-family models for rank-order relational structure, and derive sufficient statistics for interdependent ordinal judgments that do not require the assumption of comparability across raters. These statistics allow estimation of effects for a variety of plausible mechanisms governing rank structure, both in a cross-sectional context and evolving over time. The authors apply this framework to model the evolution of liking judgments in an acquaintance process and to model recall of relative volume of interpersonal interaction among members of a technology education program.
Publisher: Informa UK Limited
Date: 03-04-2015
Location: United States of America
Location: United States of America
Location: Australia
No related grants have been discovered for Pavel Krivitsky.