Restrictions of economic theory in nonparametric methods

By Rosa L. Matzkin. 1994

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Citations in the corpus

Machine Learning Methods That Economists Should Know About (2019, methodology): “As q → 0, the solution penalizes the number of non-zero covariates, leading to best subset regression (Miller [2002], Bertsimas et al.”
Semi‐Nonparametric IV Estimation of Shape‐Invariant Engel Curves (2003, background): “…illus- trates the importance of utilizing the semi-nonparametric restrictions and suggests that it would be worthwhile to further investigate the imposition of restrictions derived from economic theory in identification and estimation of econometric models, see Matzkin (1994) for example.”
Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New Environments (2007, methodology): “…the support of Zp′ and Zj ,97 so there is some overlap in the historical and policy p′ supports of Z, we may use nonparametric methods presented in Matzkin (1994) and extended by her in Chapter 73 (Matzkin) of this Handbook, based on functional restrictions (e.g., homogeneity) to construct the…”
Nonparametric estimation of an additive model with a link function (2002, background): “Stone(1994) and Newey (1997)describesplineestim atorswhoseL2 rateofconvergenceis n 2=5,butthepointwiseratesofconvergenceand asym ptoticdistributionsof splineand otherseriesestim atorsrem ain unknown.”
Representation theorem for convex nonparametric least squares (2008, methodology): “In the present context of nonparametric regression, the possibility to use the Afriat inequalities to model concavity/convexity constraints has been briefly suggested by Matzkin (1994, 1999) and Yatchew (1998); Theorem 2.1 confirms and further elaborates these conjectures.”
Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation (2007, methodology): “The chapters in the Handbook series by McFadden (1984), Heckman and MaCurdy (1986), Matzkin (1994), Blundell, MaCurdy and Meghir (2007), Reiss and Wolak (2007), Ackerberg et al. (2007), and Athey and Haile (2007) exposit detailed econometric analyses of specific economic models that are based on…”
A Simple Estimator for Binary Choice Models with Endogenous Regressors (2015, background): “Earlier results that can be reinterpreted as special cases of special regressor based identification methods include Matzkin (1992, 1994) and Lewbel (1997).”
Chapter 76 Large Sample Sieve Estimation of Semi-Nonparametric Models (2007, methodology): “In this subsection we present three empirical examples as illustration; additional ones can be found in Manski (1994), Powell (1994), Matzkin (1994), Horowitz (1998), Pagan and Ullah (1999), Blundell and Powell (2003) and other surveys on this topic.”
Nonparametric Estimation of Nonadditive Random Functions (2003, background): “(Matzkin (1994) reviews sorne of the existent literature for limited dependent variable rnodels and nonparametric regression functions.)”
A Test of Non-Identifying Restrictions and Confidence Regions for Partially Identified Parameters (2009, unknown): “This setup is employed by Roehrig (1988) and Matzkin (1994), who analyze conditions for nonparametric identification of structures where the endogenous observable variables are functions of unobservable variables and exogenous observable ones.”