"A man is worked upon by what he works on. He may carve out his circumstances, but his circumstances will carve him out as well.”
- Frederick Douglass.
GCER Fellow Alexandre Poirier's and Matthew Masten's study of treatment effects carves out the circumstances under which circumstances carve out economic behavior.
Economists handling data need to make assumptions to draw causal conclusions. For example, to evaluate the effect of participating in a job training program on unemployment duration, one has to take a stand on how program participation is related to the participants and nonparticipants' characteristics. These questions can sometimes be answered with randomized experiments, but more often economists must work with observational data. In this case, researchers often make a "quasi-randomization" assumption that allows us to analyze the data as if a certain randomized experiment was actually performed. Since an experiment was not actually performed, it is important to understand what conclusions we can draw when assumptions like quasi-randomization fail.
In two recent papers entitled "Identification of Treatment Effects under Conditional Partial Independence" and "Inference in Breakdown Frontiers" (both co-authored with Matthew Masten at Duke University), Georgetown economist and GCER Fellow Alexandre Poirier propose a framework to address the question: how sensitive are empirical results to assumptions like quasi-randomization?
Poirier and Masten first define a measure of "distance from independence" which quantifies departures from quasi-randomization. Under independence, the average effect of a treatment (such as participation in a job training program) can be recovered from the data, while under partial independence one can only recover a range of values for this average treatment effect. This range increases as one departs further from quasi-randomization. This range can be used by economists to determine the sensitivity of their results to quasi-randomization failures.
Second, they also determine the "breakdown" for different conclusions that are typically made. For example, economists are often interested in finding out whether at least half of economic agents would benefit from a treatment. Using Masten and Poirier's framework, economists can determine which set of assumptions guarantee that at least half benefit from a treatment, and which set of assumptions does not yield that conclusion. This allows researchers to assess the sensitivity of conclusions with respect to one or more assumptions that cannot be verified in the data. In particular, if a large number of different assumptions guarantee that at least half benefit, then this result can be deemed robust. Meanwhile, if very few assumptions lead to this conclusion, it will be deemed fragile. Their framework also allows researchers to examine the tradeoffs between imposing and relaxing different assumptions.
Finally, Poirier and Masten apply their method to a previous study by Blattman and Annan (Rev Econ and Stat 2010) on the effects of child soldiering on economic outcomes. The techniques of Poirier and Masten determine which conclusions in the Blattman and Annon study are more or less robust to violations of the quasi-experimental assumptions.
Previously Featured Research Profiles:
Fall 2018 Featured Research Profile: “You’re [not] fired!”–GCER Fellow Toshi Mukoyama and Sophie Osotimehin explore the dynamic linkages between employment protection regulations and firms’ innovation decisions.
Winter/Spring 2017-2018 Featured Research Profile: Child Care in Reverse: GCER Fellow Ami Ko explores the subtle effects of informal health care on the long-term care insurance market.
Fall/Winter 2016-2017 Featured Research Profile: Markets with Search and Matching Frictions: Georgetown economists James Albrecht and Susan Vroman discuss directed search in the housing market.
Fall/Winter 2015-2016 Featured Research Profile: How (not) to run a bank: Georgetown economist Martin Ravallion examines World Bank successes and failures.
Spring/Summer 2015 Featured Research Profile: Leaning in,... sort of: Georgetown economist Mary Ann Bronson explores reasons why men and women make different post-secondary educational investments.
Fall 2014 Featured Research Profile: Carbon emissions make the global economy tipsy... Harrison and Lagunoff study a "business-as-usual" scenario in a tipping model.
Spring 2014 Featured Research Profile: Collateral Damage to Standard Economic Theory... GCER Fellow Dan Cao shows how incorrect beliefs can fuel a crisis.
Fall 2013 Featured Research Profile: Oh what a tangled web we weave... Anderson and Smith explore the dilemmas of deception.
Winter/Spring 2013 Featured Research Profile: Unintended Consequences in the Struggle for Equal Rights: Anderson and Genicot explore the surprising relationship between suicides and female property rights in India.
Fall 2012 Featured Research Profile: Gale and O'Brien sing the blues over Use-or-Lose!
Spring/Summer 2012 Featured Research Profile:"What a piece of work is a man! How noble in Reason! How infinite in faculties!" ... But how much is he worth? Huggett and Kaplan provide an answer.
Winter 2012 Featured Research Profile: Happiness is in the air! Levinson uses happiness surveys to put a dollar value on air quality.
Fall 2011 Featured Research Profile: Junior, the Risky Investment, Grandma, the Insurance Contract, and other bedtime stories as told by Gete and Porchia.
Spring/Summer 2011 Featured Research Profile: Ludema, Mayda, and Mishra show that when firms talk, governments listen.
Winter 2011 Featured Research Profile: Bachmann and Bai examine the effects of wealth bias in the policy process.