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<span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt;">Dear all,</span><br>
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<span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif">Hope everyone is keeping well!</span><br>
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<div style="margin: 0px; background-color: white; color: black;"><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; color: rgb(0, 0, 0);">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</span><br>
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<div style="margin: 0px; background-color: white; color: black;"><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">"</span><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">A
simulated annealing-based algorithm for selecting balanced samples,</span><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">" </span></div>
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<div style="margin: 0px; background-color: white; color: black;"><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">and Christis Katsouris, presenting on </span></div>
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<div style="margin: 0px; background-color: white; color: black;"><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">"Structural-break Detection in Nonstationary Quantile Time Series Models."</span></div>
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<div style="margin: 0px; background-color: white; color: black;"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">P</span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">lease
see below for the details of the talks and how to join the seminar online.</span></div>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);">Have a nice week, and hope to see you at the seminar
on Thursday!</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);">Kind regards,</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 11.5pt; color: rgb(32, 31, 30); background-color: white;"><br>
</span><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);">Jessie</span><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);"><br>
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<p style="margin-top: 0px; margin-bottom: 0px;"><span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif"><em><strong></strong></em></span></p>
<span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;"><b><i>A simulated annealing-based algorithm for selecting balanced samples.</i></b></span><br>
<span style="color: rgb(0, 0, 0); font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; background-color: rgb(255, 255, 255); display: inline !important;">Francesco Pantalone</span><br>
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<div style="margin:0px"><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">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.</span></div>
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<div style="margin:0px"><span style="font-size:12pt; font-family:Calibri,Helvetica,sans-serif"></span><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;"><b><i>Structural-break Detection in Nonstationary Quantile Time Series Models</i></b></span><span><br>
<span style="color: rgb(0, 0, 0); font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; background-color: rgb(255, 255, 255); display: inline !important;">Christis Katsouris</span></span></div>
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<div style="margin:0px"><span style="font-size: 12pt; font-family: Calibri, Helvetica, sans-serif;">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. </span><span><br>
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