gov3009-l March 2009

gov3009-l@lists.fas.harvard.edu

1 participants
4 discussions

Spirling on ``Bargaining Power in Practice: US Treaty-making with American Indians, 1784--1911"

by Justin Grimmer

Dear Applied Statistics Community, Please join us this Wednesday when Arthur Spirling, Department of Government, will present ``Bargaining Power in Practice: US Treaty-making with American Indians, 1784--1911". Arthur provided the following overview for his talk: I will discuss a new data set of treaties signed 1784--1911 between the United States government and American Indian tribes, and comment on some early findings using kernel methods to analyze these texts. I particularly welcome feedback and suggestions from the ASW on the appropriateness of the techniques given the problem at hand. Arthur also provided the following abstract for a paper that is the basis for his talk: Native Americans are unique among domestic actors in that their relations with the United States government involve treaty-making, with almost 600 such documents signed between the Revolutionary War and the turn of the twentieth century. We obtain and digitize all of these treaties for textual analysis. In particular, we employ new 'kernel methods' to study the evolution of their nature over time and show that the Indian Removal Act of 1830 represents a systematic shift in language. We relate our findings to a bargaining model with the parties---government and tribes---varying in power according to contemporary political and economic events. With a mind to earlier historical and legal literatures, we also show that the 'broken' treaties do not form their own cluster in the data, and that the post-1871 'agreements' represent a straightforward continuation of earlier treaty policy in both style and substance. The Applied Statistics Workshop meets each Wednesday at 12 noon in K-354 CGIS-Knafel (1737 Cambridge St). The workshop begins with a light lunch and presentations usually start around 1215 and last until about 130 pm. All are welcome-- Justin Grimmer

15 years

Lenz on ``Getting Rich(er) in Office? Corrpution and Wealth Accumulation in Congress"

by Justin Grimmer

Dear Applied Statistics Workshop Participants, Please join us this Wednesday when Gabriel Lenz, MIT Department of Political Science, will present ``Getting Rich(er) in Office? Corruption and Wealth Accumulation in Congress", work that is joint with Kevin Lim. Gabe provided the following abstract: How corrupt is Congress? We provide an indirect test by comparing wealth accumulation from 1995 to 2005 among members of the U.S. House of Representatives and members of the public. Data on representatives are from Personal Financial Disclosure forms and data on the public are from the Panel Study of Income Dynamics (PSID). To test whether representatives accumulate wealth at a faster rate than expected, we construct counterfactuals based on the PSID with two approaches. We first use statistical models, conditioning on asset distribution over stocks, bonds, businesses, and land, as well as demographic variables. These models find representatives accumulating wealth about 20 percent faster than expected. Second, we employ matching. Unlike the modeling approach, matching finds an almost identical rate of wealth accumulation among both groups. Further analysis reveals that matching reduces bias from several incorrect functional form assumptions in the statistical models. We thus conclude that representatives report accumulating wealth at a rate consistent with similar non-representatives, suggesting no aggregate corruption. Besides examining overall wealth accumulation, we also test for effects of committee assignments, safe seats, career trajectories, and campaign contributions The Applied Statistics Workshop meets each Wednesday at 12 noon in K-354 CGIS-Knafel (1737 Cambridge St). The workshop begins with a light lunch and presentations usually start around 1215 and last until about 130 pm. Hope you can make it Cheers Justin Grimmer

15 years, 1 month

Hopkins on "Making Credible Inferences about the Effects of Local Contexts"

by Justin Grimmer

Dear Applied Statistics Workshop, Please join us this Wednesday when Dan Hopkins, Post-Doctoral Fellow at Harvard University (and soon to be Assistant Professor at Georgetown), will present "Making Credible Inferences about the Effects of Local Contexts". Dan provided the following abstract for his presentation: In the last decade, there has been an explosion of social science research exploring the influence of local contexts on attitudes and behavior. Yet such studies face methodological hurdles, including the endogeneity of individuals' moving decisions, significant measurement error, and ambiguity about their causal interpretation. This presentation reconceptualizes the effects of local contexts as an interaction between the local context and salient national issues. It then uses panel or time-series cross-sectional data to explore the impact of exogenous changes in the salience of national issues on local contextual effects. Across three empirical examples on attitudes toward immigration drawn from two countries, we observe that local contexts only correlate with attitudes when immigration is a nationally salient issue. The effects of local contexts vary in predictable ways with the topics of national politics. All politics might not be local after all. Dan provided the following paper as background for his talk: http://people.iq.harvard.edu/~dhopkins/immpap75tot.pdf The Applied Statistics Workshop meets each Wednesday in room K354, 1737 Cambridge St (CGIS-Knafel). A light lunch is served at 12 noon, with presentations usually beginning at 1215 pm and the workshop usually concludes by 130 pm. All are welcome! Cheers Justin Grimmer

15 years, 1 month

Jamie Robins on ``A Bold Vision of Artificial Intelligence and Philosophy: Finding Causal Effects Without Background Knowledge or Statistical Independences"

by Justin Grimmer

Dear Applied Statistics Workshop, Please join us this Wednesday, March 4th when Jamie Robins will present ``A Bold Vision of Artificial Intelligence and Philosophy: Finding Causal Effects Without Background Knowledge or Statistical Independences", a project that is joint with Thomas Richardson, Ilya Shpitser, and Steffen Lauritzen. Jamie provided the following abstract: I describe a statistical methodology based on philosophy, causal directed acyclic graphs, and a pinch of magic and miracle that holds the promise of making a silk purse of causal knowledge out of the sow's ear of an observational data set with no obvious structure. In 10 years or so, for better or worse, this methodology may become part of mainstream genomics. The workshop will meet at 12 noon in room K-354, CGIS-Knafel (1737 Cambridge St) with a light lunch served. The presentation will begin at 1215 and usually ends around 130 pm. All are welcome Cheers, Justin Grimmer

15 years, 1 month

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gov3009-l March 2009