Presentations

Daniel O'Brien (Northeastern University) - Ecometrics in the Age of Big Data: Measuring and Assessing Neighborhood Characteristics Using Administrative Records Wednesday, March 12, 2014

Presenter: Daniel O'Brien

Abstract: The collection of large-scale administrative records in electronic form by many cities provides a new opportunity for the measurement and longitudinal tracking of neighborhood characteristics, but one that will require novel methodologies that convert such data into research-relevant measures. The current paper illustrates these challenges by developing measures of physical disorder from Boston’s “Constituent Relationship Management” (CRM) system. A sixteen-month archive of...

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Ned Hall (Harvard) - In Praise of Causal Mechanisms Wednesday, March 5, 2014

Abstract: Consider two theses about causation: (1) Causes are connected to their effects by way of mediating causal mechanisms or processes. (2) Scientific inquiry aims (at least in part) at discerning and describing the causal structure of our world. Some of the best contemporary work on causation claims—often implicitly, but sometimes quite explicitly—that, in giving an account of causation, we should sacrifice (1) for the sake of producing an account that makes the best sense of (2). I will first try to...

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Adam Glynn (Emory Universiity) - Front-Door Difference-in-Differences Estimators: The Effects of Early In-person Voting on Turnout (joint work with Konstantin Kashin) Wednesday, February 26, 2014:

Presenter: Adam Glynn

Abstract: In this paper, we develop front-door difference-in-differences estimators that utilize information from post-treatment variables in addition to information from pre-treatment covariates. Even when the front-door criterion does not hold, these estimators allow the identification of causal effects by utilizing assumptions that are analogous to standard difference-in-differences assumptions. We also demonstrate that causal effects can be bounded by front-door and front-door difference-in-differences estimators...

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James Honaker (Harvard) - Sorting Algorithms for Qualitative Data to Recover Latent Dimensions with Crowdsourced Judgments Wednesday, February 12, 2014:

Abstract: The Quicksort and Bubble Sort algorithms are commonly implemented procedures in computer science for sorting a set of numbers from low to high in an efficient number of processes using only pairwise comparisons. Because of such algorithms’ reliance on pairwise comparison, they lend themselves to any implementation where a simple judgment requires selecting a winner. We show how such algorithms, adapted for stochastic measurements, are an efficient way to harness human ”crowdsourced” coders who are...

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Tyson Belanger (Harvard) - Fear, Hope, and War: Positive Inducements Help Win Wars Wednesday, February 5, 2014:

Abstract:  How do states win wars against other states? We have three explanations. By selection effects, states choose more winnable wars. By warfighting, states use negative inducements so enemies fear fighting. And by peacemaking, states use positive inducements so enemies hope for settling. This article investigates peacemaking. It theorizes that states optimally produce war influence only if they efficiently combine both warfighting negative and peacemaking positive inducements. It measures positive inducements by law of war compliance, where...

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Patrick Lam (Harvard) - Voter Persuasion in Compulsory Electorates: Evidence from a Field Experiment in Australia Wednesday, January 29, 2014:

Abstract: Most of the literature on grassroots campaigning focuses on mobilizing potential supporters to turn out to vote. The actual ability of partisan campaigns to boost support by changing voter preferences is unclear. We present the results of a field experiment the Australian Council of Trade Unions (ACTU) ran during the 2013 Australian Federal Election. The experiments were designed to minimize the conservative (the Coalition) vote as part of one of the largest and most extensively documented voter persuasion...

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Not in My Backyard: Understanding Local Opposition to Undocumented Immigration Using a National Survey Experiment- Author: Jason Anastasopoulos Wednesday, December 4, 2013
Author: Jason Anastasopoulos

Abstract: Understanding what motivates animus toward undocumented immigrants presents several empirical challenges.  Estimates of undocumented immigrants at the state and metropolitan area level are unreliable, rendering studies which base conclusions on them questionable at best. Furthermore, because undocumented immigrants mostly come from Latin American countries, assessing the role that undocumented immigrant characteristics such as race or ethnic background...
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Consumer Demand and Welfare Estimation in a Heterogeneous Population- Presenter: Stefan Hoderlein Wednesday, November 20, 2013

Presenter: Stefan Hoderlein 

Abstract: This is an overview about own recent econometric work related to the modeling of heterogeneity in applied consumer demand models. The focus will be on non-parametric random coefficient models. The main application will come from estimating gasoline demand; in particular, estimating the distribution of welfare effects of a 5% gasoline price change.

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Surrogate Measures and Consistent Surrogates- Presenter: Tyler VanderWeele Wednesday, November 13, 2013

Presenter: Tyler VanderWeele 

Abstract: Surrogates which allow one to predict the effect of the treatment on an outcome from the effect of the treatment on the surrogate are of interest when it is difficult or expensive to measure the primary outcome. There have, however, been several instances of drugs that have been approved for use on the grounds of randomized trials using surrogate outcomes, that have subsequently led to public health catastrophes, costing thousands of lives. It is now clear that the use of surrogates can...

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Scalable Analysis of Conflict Behavior & Decision-Making- Presenter: Amy Sliva Wednesday, November 6, 2013

Presenter: Amy Sliva 

Abstract: The ability to model, forecast, and understand the behavioral dynamics and decision-making patterns of human agents has applications in many contexts. One particularly salient domain is the field of international security where artificial intelligence models can be leveraged to analyze complex and uncertain security situations. Real world datasets can contain 10^30,000 possible behaviors—requiring efficient techniques to manage the confluence of cultural, social, economic, political, and...

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