Comparing IV With Structural Models: What Simple IV Can and Cannot Identify

By James J. Heckman, Sergio S. Urzúa. Journal of Econometrics, 2010

356 citations recorded by the source corpus.

This paper compares the economic questions addressed by instrumental variables estimators with those addressed by structural approaches. We discuss Marschak’s Maxim: estimators should be selected on the basis of their ability to answer well-posed economic problems with minimal assumptions. A key identifying assumption that allows structural methods to be more informative than IV can be tested with data and does not have to be imposed.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/3498db721ad3b460c0077b1463e1d6a403ec4599

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

Citations in the corpus

Beyond LATE with a discrete instrument. Heterogeneity in the quantity-quality interaction of children (2012, background): “Notable exceptions include Heckman and Vytlacil (2007), Heckman, Urzua, and Vytlacil (2006) and Heckman and Urzua (2010).”
Economic Returns to Education: What We Know, What We Don't Know, and Where We Are Going Some Brief Pointers (2011, unknown): “Heckman and Urzua (2009) outline a number of potential problems associated with IV estimation; weak instruments can give biased estimates; IV estimates rest on strong, a priori data assumptions; in a heterogeneous model, different”
Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT (2014, background): “Partly for these reasons a number of authors have called into question the usefulness of LATE for program evaluation (Heckman 1997; Deaton 2009; Heckman and Urzúa 2010).”
Field of Study, Earnings, and Self-Selection* (2016, unknown): “Heckman et al. (2006) and Heckman and Urzua (2010) discuss the challenges to identification and interpretation of treatment effects in such models.”
Education and entrepreneurial choice: An instrumental variables analysis (2010, unknown): “Other authors have used regional and legal variations in education as instruments, which also are not immune to criticism (Deaton, 2009; Heckman and Urzua, 2009; The Economist, 2009).”
From the Editors: Endogeneity in international business research (2012, background): “The systematic manner in which the underlying data emerge needs to be considered before the first test is performed (Heckman & Urzua, 2009).”
Community Colleges and Upward Mobility (2019, unknown): “2 Methodologically, this new approach overcomes a challenge in the instrumental variables (IV) literature: standard IV methods like two-stage least squares (2SLS) do not generally recover causal effects of one alternative versus another when individuals face multiple treatment alternatives and reap ”
Beyond LATE with a Discrete Instrument (2017, methodology): “Recent work has proposed several tests of the external validity of LATE (see, e.g., Heckman and Schmierer 2010; Heckman et al. 2010; Angrist and Fernandez-Val 2013).”
Handbook on Impact Evaluation: Quantitative Methods and Practices (2009, background): “…approach (Chapter 2), which is strongly advocated in some quarters (Duflo and Kremer 2003, Miguel and Kremer 2004, Banerjee et al. 2009), although subject to criticism by others who assert the continuing value of observational data (Deaton 2009, Heckman and Urzua 2009, Imbens 2009, Pritchett 2009).”
Comparing and combining process-based crop models and statistical models with some implications for climate change (2017, background): “…approaches roughly align with what economists call structural and reduced form methods in applied economics, or what others call model based and design based approaches (Card 2012), a subject of considerable methodological debate (Freedman 1991, Heckman and Urzua 2010, Deaton 2010, Imbens 2010).”