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Business Analytics Seminars

The seminars are on Fridays at 11am in Room 1050, Abercrombie Building (H70), unless otherwise specified.

The seminar organiser is A/Prof Peter Radchenko.

Upcoming Seminars


23rd Aug 2017 - 04:00 pm

Venue: Room 5070 Abercrombie Building (H70)

Speaker: Professor Moshe Haviv, Hebrew University of Jerusalem

Title: Externalities, Optimization And Regulation In Queues

Abstract: The academic research on queues deals mostly with waiting. Yet, the externalities , namely the added waiting time an arrival inflicts on others, are of no less, if not of more, importance. The talk will deal mostly with how the analysis of the externalities leads to the socially optimal behavior, while solving queueing dilemmas such as whether or not to join a queue or from which server to seek service at. Customers, being selfish, do not mind the externalites they impose on others. We show how in queues too, internalizing the externalities leads to self regulation. In this setting selecting the service regime is one of the tools for regulation.(Joint with Binyamin Oz, The University of Auckland)


25th Aug 2017 - 11:00 am

Venue: Rm 1050 Abercrombie Bldg H70

Speaker: Dr Nadja Klein, Melbourne Business School; University of Melbourne; Carlton Vic 3053

Title: Scale-Dependent Priors for Variance Parameters in Structured Additive Distributional Regression

The selection of appropriate hyperpriors for variance parameters is an important and sensible topic in all kinds of Bayesian regression models involving the specification of (conditionally) Gaussian prior structures where the variance parameters determine a data-driven, adaptive amount of prior variability or precision. We consider the special case of structured additive distributional regression where Gaussian priors are used to enforce specific properties such as smoothness or shrinkage on various effect types combined in predictors for multiple parameters related to the distribution of the response. Relying on a recently proposed class of penalised complexity priors motivated from a general set of construction principles, we derive a hyperprior structure where prior elicitation is facilitated by assumptions on the scaling of the different effect types. The posterior distribution is assessed with an adaptive Markov chain Monte Carlo scheme and conditions for its propriety are studied theoretically. We investigate the new type of scale-dependent priors in simulations and two challenging applications, in particular in comparison to the standard inverse gamma priors but also alternatives such as half-normal, half-Cauchy and proper uniform priors for standard deviations.

 


1st Sep 2017 - 11:00 am

Venue: Rm 1050 Abercrombie Bldg H70

Speaker: Dr Wendun Wang, Erasmus School of Economics; Erasmus University; Rotterdam, Netherlands

Title: Heterogeneous Structural Breaks in Panel Data Models

This paper provides a new model and a new estimation procedure for panel data that allow us to discern heterogeneous structural breaks. In many applications, there is a good reason to suspect that structural breaks occur at different time points across individual units and the sizes of the breaks differ too. We model individual heterogeneity to have a grouped pattern such that individuals within a given group share the same regression coefficients. For each group, we allow common structural breaks in the coefficients, while both the number of breaks and the break points can differ across groups. We develop a hybrid procedure of the grouped fixed effects and adaptive group fused Lasso (least absolute shrinkage and selection operator) to estimate the model. The grouped fixed effects approach is used to estimate the group structure and the adaptive group fused Lasso is used to detect the structural breaks and obtain coefficient estimates. We show that our method can consistently identify the latent group structure, detect structural breaks, and estimate the regression parameters. Monte Carlo results demonstrate good performance of the method in finite sample. We apply our method to two cross-country empirical studies and illustrate the importance of taking heterogeneous structural breaks into account.