# Social Science Statistics Blog

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25 March 2013

### App Stats: Fowler and Hall on "Do Legislators Cater to the Priorities of Their Constituents?"

We hope you can join us this Wednesday, March 27, 2013 for the Applied Statistics Workshop. Anthony Fowler and Andrew B. Hall, Ph.D. Candidates from the Department of Government at Harvard University, will give a presentation entitled "Do Legislators Cater to the Priorities of Their Constituents?". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Do Legislators Cater to the Priorities of Their Constituents?"
Anthony Fowler and Andy Hall
Government Department, Harvard University
CGIS K354 (1737 Cambridge St.)
Wednesday, March 27th, 2013 12.00 pm

Abstract:

> Republican and Democratic legislators vote differently on a large number of bills even when representing constituents of identical preferences. Because constituencies care about some issues more than others, representatives may give short shrift to the district's preferences on some topics while carefully mirroring them on others. The more a district cares about an issue, the more loyally we should see its legislators voting. As a consequence, we should expect the partisan gap in representation -- the difference in voting behavior between a Democrat and a Republican representing the same constituents -- to shrink on issues of greater concern to the district. We test this hypothesis in eight issue areas: agriculture, civil rights, defense, education, energy, public transportation, senior citizens' issues, and welfare. Contrary to expectation, we find little evidence that representational quality improves when constituents have strong personal interests. Across all issues examined, the representational gap between the parties is massive and does not shrink meaningfully in especially-interested districts.

Posted by Konstantin Kashin at 10:34 AM

11 March 2013

### App Stats: Chamberlain on "Predictive Effects of Teachers and Schools on Test Scores, College Attendance, and Earnings"

We hope you can join us this Wednesday, March 13, 2013 for the Applied Statistics Workshop. Gary Chamberlain, Louis Berkman Professor of Economics from the Department of Economics at Harvard University, will give a presentation entitled "Predictive Effects of Teachers and Schools on Test Scores, College Attendance, and Earnings". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Predictive Effects of Teachers and Schools on Test Scores, College Attendance, and Earnings"
Gary Chamberlain
Department of Economics, Harvard University
CGIS K354 (1737 Cambridge St.)
Wednesday, March 13, 2013 12.00 pm

Abstract:

> I study predictive eﬀects of teachers and schools on test scores in fourth through eighth grade and outcomes later in life such as college attendance and earnings. The predictive eﬀects have the following form: predict the fraction of a classroom attending college at age 20 given the test score for a diﬀerent classroom in the same school with the same teacher, and given the test score for a classroom in the same school with a diﬀerent teacher. I would like to have predictive eﬀects that condition on averages over many classrooms, with and without the same teacher. I set up a factor model which, under certain assumptions, makes this feasible. Administrative school district data n combination with tax data were used to calculate estimates and do inference.

Posted by Konstantin Kashin at 4:14 AM

4 March 2013

### App Stats: Goodman on "Seeing More in Data"

We hope you can join us this Wednesday, March 6, 2013 for the Applied Statistics Workshop. Alyssa Goodman, a Professor of Astronomy from the Harvard-Smithsonian Center for Astrophysics at Harvard University, will give a presentation entitled "Seeing More in Data". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Seeing More in Data"
Alyssa A. Goodman
Harvard-Smithsonian Center for Astrophysics
CGIS K354 (1737 Cambridge St.)
Wednesday, March 6th, 2013 12.00 pm

Abstract:

> Some scientists still think that good data visualization is only necessary when presenting work to "the public." In truth, thinking hard about how to learn the most from any data set should always involve some form of graph, map, chart, or other visual statistical display. This talk will demonstrate how visualization techniques that include so-called "linked views" offer new insights to researchers visualizing large and/or diverse data sets. In particular, the talk will highlight a few high-dimensional visualization examples where ideas about linked views first put forth by John Tukey are extended beyond two-dimensional displays and point clouds. Examples will be principally drawn from astronomy and medical imaging, and software highlighted will include the Universe Information System known as "WorldWide Telescope" (worldwidetelescope.org) and a new python-based linked-view system called "Glue" (glueviz.org).

Posted by Konstantin Kashin at 1:43 AM