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Seminar Series: Spring 2010
The Department of Management Science and Statistics Seminar Series will occur on Fridays throughout the semester. For additional information contact Dr. Kefeng Xu, (210) 458-5388.

Friday, Jan. 15, 2010 (Time and Location: 2-3 p.m., Executive Conference Room BB 4.02.10)

  • Presenter: Professor Sat Narain Gupta Department of Mathematics and Statistics The University of North Carolina at Greensboro (Note: Professor Sat Gupta is also the Editor-in-Chief of Journal of Statistical Theory and Practice.)

  • Presentation Title: Additive vs. Multiplicative Scrambling in Two-Step Optional Randomized Response Models

  • Abstract: Randomized response models, introduced by Warner (1965, JASA), are important data collection tools in survey sampling when the researcher is interested in data acquisition on sensitive questions. An optional randomized response model, introduced by Gupta, Gupta and Singh (2002, JSPI), is a variation of the usual randomized response model that helps improve the estimation of the mean of a sensitive question. The basic premise in these models is that a question may be sensitive for one respondent but may not be sensitive for another, and hence the choice to provide a truthful response or a scrambled response should be left to the respondent. In doing so, there is an opportunity to estimate the sensitivity level of a question in addition to the estimation of the mean. Gupta, Shabbir and Sehra (2010, JSPI) consider two-step optional RRT models to simultaneously estimate the mean and the sensitivity level of a quantitative- response sensitive question. In a two-step model, a randomly selected pool of respondents is asked to tell the truth and the rest are asked to provide a truthful response if they consider the question to be non-sensitive and a scrambled response if they consider the question to be sensitive. The researcher will not know who provided a truthful response and who provided a scrambled response, so anonymity is maintained.

    In this talk we will consider parameter estimation for an optional RRT model using additive scrambling. We will note that additive scrambling performs better than multiplicative scrambling.

     

Friday, Feb. 26, 2010 (Time and Location: 2-3 p.m., Executive Conference Room BB 4.02.10)

  • Presenter: Dr. Long Liu, Assistant Professor, Department of Economics, College of Business, University of Texas at San Antonio. Co-Author: Chihwa Kao of Syracuse University.

  • Presentation Title: Estimating and Testing in Panel Data Modes in the Presence of Autoregressive Error

  • Abstract: This paper studies the estimation and inference of panel data models without any prior knowledge of whether the error term is stationary or nonstationary. We propose new test statistics that use feasible generalized least squares (FGLS) estimator. The proposed tests have the standard normal limiting distribution and valid for both I(0) and I(1) errors.


Friday, Mach 26, 2010 (Time and Location: 2-3 p.m., Executive Conference Room BB 4.02.10)

  • Presenter: TBA

  • Presentation Title: TBA

  • Abstract: TBA

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