401(K) Plans and Tax-Deferred Saving

By J. Poterba, Steven F. Venti, David A. Wise. 1992

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Citations in the corpus

Double/De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers (2018, methodology): “We follow the identification strategy of Poterba and Venti (1994) and Poterba et al. (1995), who assume selection on observables.”
Double/Debiased Machine Learning for Treatment and Causal Parameters (2016, methodology): “ty of 401(k) eligibility is that eligibility may only be taken as exogenous after conditioning on income and other variables related to job choice that may correlate with whether a rm oers a 401(k). [47] and [48] and many subsequent papers adopt this argument but control only linearly for a small nu”
Semiparametric instrumental variable estimation of treatment response models (2003, background): “These data were prepared for Poterba et al. (1996). The observational units are household reference persons aged 25-64 and spouse if present.”
Program evaluation with high-dimensional data (2013, methodology): “They applied it to the specific problem of the linear instrumental variables model with many instruments where the nuisance function h0 is the optimal 3See also Poterba, Venti, and Wise (1994; 1995; 1996; 2001), Abadie (2003), Benjamin (2003), and Ogburn et al. (2015) among others.”
The Effects of 401(K) Participation on the Wealth Distribution: An Instrumental Quantile Regression Analysis (2004, methodology): “Using the reasoning of Poterba et al. (1994, 1995, 1996) and Abadie (2003) outlined above, we use 401(k) eligibility as an instrument for 401(k) participation in order to estimate the effect of participating in a 401(k) on various measures of wealth. To do this, we employ a model and an estimator de”
Double machine learning for treatment and causal parameters (2016, methodology): “Finally, it is interesting that these results are also broadly consistent with those reported in the original work of [45] and [46] which used a simple intuitively motivated functional form, suggesting that this intuitive choice was sufficiently flexible to capture much of the confounding variation ”
The Effects of Financial Education in the Workplace: Evidence from a Survey of Employers (2009, unknown): “The effects of these features are, of course, of independent interest, and have been the subject of several prior analyses (see Poterba, Venti, and Wise, 1994, Papke, Petersen, and Poterba, 1993, Papke, 1995, Andrews, 1992, Kusko, Poterba, and Wilcox, 1993, and Scott, 1994).”
Threshold Regression with Endogeneity (2017, unknown): “This sample is often referred to as the 1991 SIPP, and is used extensively in the literature to examine the effect of 401(k) plans on wealth; see, inter alia, Benjamin (2003), Engen and Gale (2000), Engen et al. (1996) and Poterba et al. (1994, 1995, 1998).”
Do 401(k) contributions crowd out other personal saving (1995, methodology): “5 This method was used by Venti and Wise (1992) to evaluate the saving effect of IRAs, and in an earlier paper by Poterba et al. (1994) that considered 401(k) plans. As explained in Venti and Wise (1993), the comparisons that are made in this analysis are the same as the key comparisons made in more”
Double/debiased machine learning for treatment and structural parameters (2017, unknown): “To overcome the lack of random assignment, we follow the strategy developed in Poterba et al. (1994a) and Poterba et al. (1994b). In these papers, the authors use data from the 1991 Survey of Income and Program Participation and argue that eligibility for enrolling in a 401(k) plan in this data can ”