[Turing-Southampton] S3RI seminar: Francesco Pantalone and Christis Katsouris (University of Southampton)

[Chieh-Hsi Wu]

Dear all,

Hope everyone is keeping well!

At the S3RI seminar this week (Thursday 11 November, 2 PM), we have our own members from S3RI, Dr Francesco Pantalone, giving a talk on

"A simulated annealing-based algorithm for selecting balanced samples,"

and Christis Katsouris, presenting on

"Structural-break Detection in Nonstationary Quantile Time Series Models."

Please see below for the details of the talks and how to join the seminar online.



Have a nice week, and hope to see you at the seminar on Thursday!



Kind regards,

Jessie



A simulated annealing-based algorithm for selecting balanced samples.
Francesco Pantalone

Balanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm.


Structural-break Detection in Nonstationary Quantile Time Series Models
Christis Katsouris

In this paper, we propose an econometric framework for structural break detection in nonstationary quantile predictive regressions. We establish the asymptotic distributions for a class of Wald and fluctuation type statistics based on both the ordinary least squares (OLS) estimator and the endogenous instrumental variable regression (IVX) estimator proposed by Phillips, P. C. B and Magdalinos, T. (2009). Although the asymptotic distribution of these test statistics appears to depend on the chosen estimator, the IVZ based tests are shown to be asymptotically nuisance parameter-free regardless of the degree of persistence. The finite-sample performance of both tests is evaluated via simulation experiments and bootstrap based-inference techniques. An empirical application to house pricing index returns demonstrates the practicality of the proposed structural break testing procedures for regression quantiles of nonstationary time series data.


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