gov3009-l September 2012

gov3009-l@lists.fas.harvard.edu

1 participants
5 discussions

Applied Statistics Workshop: Luke Miratrix on Wed., Sept. 26

by Konstantin Kashin

*Dear all, Please join us for the Applied Statistics Workshop (Gov 3009) this Wednesday, September 26 from 12.00 - 1.30 pm in CGIS Knafel Room 354. Luke Miratrix, Assistant Professor of Statistics in the Department of Statistics at Harvard University, will give a presentation entitled "Random Weight Estimators: Adjusting Randomized Trials Without Using Observed Outcomes". As always, a light lunch will be provided. Abstract:* To increase the precision of a randomized trial, experimenters often adjust > estimates of treatment effects using baseline covariates thought to predict > the outcome of interest. In a previous paper, we proved that even under the > Neyman-Rubin model, if the covariates and the method for adjustment are > determined before randomization, this process can increase precision in a > manner quite similar to a comparable blocked experiment. Typically, > however, experimenters wish to adjust for the covariates that are most > imbalanced between treatment and control, given the realized randomization. > This leads to a much vexed variable selection problem that depends on the > observed treatment assignment. To understand the issues behind this > process, we examine a class of estimators we call "Random Weight > Estimators" that adjust treatment effect estimates by weighting units with > weights depending on a function on treatment assignment and covariates. > While similar in spirit to blocking, these estimators can be applied "after > the fact,'' i.e., after randomization has occurred, allowing them to > naturally adapt to the observed treatment assignment. They can also adjust > for many different covariates at once, including continuous ones. This > class is quite general, and it includes traditional methods such as > ordinary linear regression. Using our framework, we show, under the > Neyman-Rubin model, how one can easily introduce potential bias using what > would seem to be legitimate and simple approaches, especially in small and > midsize experiments. Care must be taken with many forms of adjustment, even > if an approach is selected without regard to any actual outcomes. We also > extend this methodology to survey experiments, giving an appropriate and > near-unbiased estimator for the treatment effect of a parent population. > Throughout the talk, we illustrate this overall framework. ** ** An up-to-date schedule for the workshop is available at http://www.iq.harvard.edu/events/node/1208. ** ** Best, Konstantin -- Konstantin Kashin Ph.D. Candidate in Government Harvard University Mobile: 978-844-0538 E-mail: kkashin(a)fas.harvard.edu Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashin/>

11 years, 7 months

Applied Statistics Workshop: Rich Nielsen on Wed., Sept. 19

by Konstantin Kashin

Dear all, Please join us for the Applied Statistics Workshop (Gov 3009) this Wednesday, September 19 from 12.00 - 1.30 pm in CGIS Knafel Room 354. Rich Nielsen <http://people.fas.harvard.edu/~rnielsen/>, a Ph.D. candidate from the Department of Government at Harvard University, will give a practice job talk entitled "Jihadi Radicalization of Muslim Clerics". As always, a light lunch will be provided. Abstract: ** > This paper explains why some Muslim clerics adopt the ideology of militant > Jihad while others do not. I argue that clerics strategically adopt or > reject Jihadi ideology because of career incentives generated by the > structure of cleric educational networks. Well-connected clerics enjoy > substantial success at pursuing comfortable careers within state-run > religious institutions and they reject Jihadi ideology in exchange for > continued material support from the state. Clerics with poor educational > networks cannot rely on connections to advance through the state-run > institutions, so many pursue careers outside of the system by appealing > directly to lay audiences for support. These clerics are more likely to > adopt Jihadi ideology because it helps them demonstrate to potential > supporters that they have not been theologically coopted by political > elites. I provide evidence of these dynamics by collecting and analyzing > 29,430 fatwas, articles, and books written by 91 contemporary clerics. > Using statistical natural language processing, I measure the extent to > which each cleric adopts Jihadi ideology in their writing. I combine this > with biographical and network information about each cleric to trace the > process by which poorly-connected clerics become more likely to adopt > Jihadi ideology. An up-to-date schedule for the workshop is available at http://www.iq.harvard.edu/events/node/1208. Best, Konstantin -- Konstantin Kashin Ph.D. Candidate in Government Harvard University Mobile: 978-844-0538 E-mail: kkashin(a)fas.harvard.edu Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashin/>

11 years, 7 months

Lost Iphone Charger

by Konstantin Kashin

Hi all, Rich Nielsen indicated that he found a " white plug-to-usb device in the back center plug of K354" (and that it's likely for an iphone). If you are missing this, please email him directly at nielsen.rich(a)gmail.com. -Konstantin -- Konstantin Kashin Ph.D. Candidate in Government Harvard University Mobile: 978-844-0538 E-mail: kkashin(a)fas.harvard.edu Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashin/>

11 years, 7 months

Applied Statistics Workshop: Jamie Robins on Wed., Sept. 12

by Konstantin Kashin

Dear all, Please join us for the Applied Statistics Workshop (Gov 3009) this Wednesday, September 12 from 12.00 - 1.30 pm in CGIS Knafel Room 354. Jamie Robins <http://www.hsph.harvard.edu/faculty/james-robins/>, Professor of Epidemiology at the Harvard School of Public Health, will give a presentation entitled "A Simple Unification of the Potential Outcome and Causal Graph Approaches to Causal Inference". As always, a light lunch will be provided. Abstract: ** > Potential outcomes are extensively used within statistics, epidemiology, > and political science for reasoning about causation. Directed acyclic > graphs are another formalism used to represent causal systems. They are > extensively used in computer science, bioinformatics, sociology and > epidemiology. It is natural to wish to unify them. We present a simple approach to this unification. The approach is based on > the idea of splitting nodes to construct graphs whose nodes are potential > outcomes. The resulting graph can be used to read off counterfactual > independencies. These independencies are satisfied by all previously > proposed graphical and nongraphical causal models. We review many examples > to illustrate the power of this approach. This is joint work with Thomas Richardson at the University of Washington. An up-to-date schedule for the workshop is available at http://www.iq.harvard.edu/events/node/1208. Best, Konstantin -- Konstantin Kashin Ph.D. Candidate in Government Harvard University Mobile: 978-844-0538 E-mail: kkashin(a)fas.harvard.edu Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashin/>

11 years, 7 months

Applied Statistics Workshop: Michael Grubb on Wed., Sept. 5

by Konstantin Kashin

Dear all, Please join us for the first session of the Applied Statistics Workshop (Gov 3009) this Wednesday, Sept. 5 from 12.00 - 1.30 pm in CGIS Knafel Room 354. Michael Grubb <http://www.mit.edu/~mgrubb/>, an Assistant Professor of Applied Economics from the MIT Sloan School of Management will give a presentation entitled "Cellular Service Demand: Biased Beliefs, Learning, and Bill Shock <http://www.mit.edu/~mgrubb/GrubbOsborne.pdf>". As always, a light lunch will be provided. Abstract: By April 2013, the FCC's recent bill-shock agreement with cellular carriers > requires consumers be notified when exceeding usage allowances. Will the > agreement help or hurt consumers? To answer this question, we estimate a > model of consumer plan choice, usage, and learning using a panel of > cellular bills. Our model predicts that the agreement will lower average > consumer welfare by $2 per year because firms will respond by raising > monthly fees. Our approach is based on novel evidence that consumers are > inattentive to past usage (meaning that bill-shock alerts are informative) > and advances structural modeling of demand in situations where multi-part > tariffs induce marginal-price uncertainty. Additionally, our model > estimates show that an average consumer underestimates both the mean and > variance of future calling. These biases cost consumers $42 per year at > existing prices. Moreover, absent bias, the bill-shock agreement would have > little to no effect. Note that this work is joint with Matthew Osborne at the Bureau of Economic Analysis. An up-to-date schedule for the workshop is available at http://www.iq.harvard.edu/events/node/1208. Best, Konstantin -- Konstantin Kashin Ph.D. Candidate in Government Harvard University Mobile: 978-844-0538 E-mail: kkashin(a)fas.harvard.edu Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashin/>

11 years, 7 months

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gov3009-l September 2012