7. Assessing Bias in the Estimation of Causal Effects: Rosenbaum Bounds on Matching Estimators and Instrumental Variables Estimation with Imperfect Instruments

By Thomas A. DiPrete, M. Gangl. 2004

764 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/43d069cee8ae403ac009f89a520bb63ea1e543bb

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Citations in the corpus

Food standards, certification, and poverty among coffee farmers in Uganda (2015, methodology): “To test the robustness of our results we calculate Rosenbaum bounds for hidden bias (DiPrete & Gangl, 2004; Becker & Caliendo, 2007).”
Collective Action and Community Development: Evidence from Self-Help Groups in Rural India (2013, methodology): “We use Rosenbaum’s bounding approach (Becker and Caliendo 2007; DiPrete and Gangl 2004; Rosenbaum 2002).”
The Effects of Derivatives on Firm Risk and Value (2011, background): “However, following DiPrete and Gangl (2004), we can compare the change in inferences which is potentially caused by unobserved variables, given by the Rosenbaum bounds, to the equivalent effect of observed variables, since we have estimates of the effect of the observables on the decision to use…”
The early socioeconomic effects of teenage childbearing: A propensity score matching approach (2010, methodology): “In this regard, while not calibrating the exact size of the true effect of teenage childbearing in the presence of unobserved heterogeneity, the Rosenbaum bounds method provides a basis for assessing the selection bias problem by making explicit the extent to which the ignorable treatment assignment”
How Learning a Musical Instrument Affects the Development of Skills (2013, positive): “21As an additional test, we can show that our results are robust to a sensitivity analysis using Rosenbaum bounds (DiPrete and Gangl, 2004).”
Additionality and the Adoption of Farm Conservation Practices (2013, methodology): “We conduct a Rosenbaum bounds sensitivity analysis to estimate the extent to which selection on unobservables may bias the estimates of the ATT (Rosenbaum 2002; DiPrete and Gangl 2004).”
Non-farm work and food security among farm households in Northern Ghana (2011, background): “15 DiPrete and Gangl (2004) have indicated that the Rosenbaum bounds are a worst-case scenario.”
Chief Executive Officer Equity Incentives and Accounting Irregularities (2010, methodology): “…bias that might exist, because of endogenous matching of executives and equity-incentive contracts and other similar factors.28 Rosenbaum (2002) and DiPrete and Gangl (2004) note that although propensity-score matching effectively alleviates 28 It is quite likely that hidden bias is present in…”
The Effects of Regulatory Scrutiny on Tax Avoidance: An Examination of SEC Comment Letters (2016, background): “Mean bias does not exceed 10 percent for any covariate, suggesting that we have reasonable balance (Diprete and Gangl 2004).”
Design Sensitivity and Efficiency in Observational Studies (2010, background): “…et al. (1959), Rosenbaum and Rubin (1983), Yanagawa (1984), Gastwirth (1992), Marcus (1997), Lin, Psaty, and Kronmal (1998), Robins, Rotnitzky, and Scharfstein (1999), Copas and Eguchi (2001), Imbens (2003), Diprete and Gangl (2004), Wang and Krieger (2006), and Gustafson and Greenland (2010).”
Evaluation of biodiversity policy instruments: what works and what doesn't? (2012, methodology): “Because conditional independence assumption which justifies the validity of the matching estimators is untestable, Rosenbaum’s bounds approach is one common method for dealing with omitted variables (DiPrete and Gangl, 2004).”
CEO After-Tax Compensation Incentives and Corporate Tax Avoidance (2014, positive): “32 According to DiPrete and Gangl (2004), the procedure works by determining the bounds for the significance level of the test of the null hypothesis for the case where the unobservable effect is so strong that knowledge of the unobservable effect would almost perfectly predict which pair of matched”
Labour Market Flexibilization and its Consequences in Italy (2009, background): “The control group is constructed via a statistical match of persons with the same character istics (Becker and Ichino, 2002; DiPrete and Gangl, 2004).”
On the Use of Instrumental Variables in Accounting Research (2010, methodology): “Finally, it is important to assess the potential impact of unobserved confounding variables using techniques such as those develop by Frank (2000), Rosenbaum (2002), and DiPrete and Gangl (2004).”