Semiparametric Regression for the Applied Econometrician

By Fabio Trojani. 2006

282 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fa73e7a25abff79f46837569442f9bb396c0c110

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Citations in the corpus

Too Much Finance? (2012, unknown): “Formally, we use the di¤erencing procedure suggested by Yatchew (2003) and approximate the functional space with a penalized spline smoother (Wand, 2005) to estimate di¤erent variants of the following model: GRi = 0 +Xi + f(PCi) + "i: (3) When we estimate the model of column 6, Table 1 without…”
Nonparametric and Semiparametric Models (2004, methodology): “For general aspects on semiparametric regression we refer to the textbooks of Pagan & Ullah (1999), Yatchew (2003), Ruppert, Wand & Carroll (1990). Comprehensive presentations of the generalized linear model can be found in Dobson (2001), McCullagh & Nelder (1989) and Hardin & Hilbe (2001).”
International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food (2012, unknown): “Third, we have evidence from studies of different countries and over different periods, that the Engel curve for food is log-linear and stable, both over time and across societies (Banks et al., 1997; Beatty and Larsen, 2005; Blundell et al., 1998; Leser, 1963; Working, 1943; Yatchew, 2003).”
Who Marries Whom and Why (2006, background): “Yatchew (2003) provides an excellent overview of these techniques.”
A difference based approach to the semiparametric partial linear model (2011, unknown): “In this paper, instead of focusing on the linear component as in [34, 35], we treat estimation of both the linear and the nonparametric components.”
Series estimation under cross-sectional dependence (2013, methodology): “We apply our methodology in two illustrative empirical examples, using (22) with data from Yatchew (2003). Series”
Too much finance? (2015, unknown): “Formally, we use the differencing procedure suggested by Yatchew (2003) and approximate the functional space with a penalized spline smoother (Wand 2005) to estimate different Table 3 Tests for an inverse U-shape (1) (2) (3) (4) (5) Slope at PCmin 3.52*** 3.68*** 3.91*** 3.61** 7.20*** (1.41)…”
A Comparison of the Nonparametric Regression Models using Smoothing Spline and Kernel Regression (2007, background): “The kernel function should be symmetric (see [7] and [8] ).”
Nonparametric Shape-Restricted Regression (2017, methodology): “of the predictor variables is ordered, LS estimation under the unordered weak majorization partial order can be used to estimate f. Constraints like (50) appear quite often in econometrics; see e.g., [145] and the references therein. Quasiconvexity. A function f : Rd !R is quasiconvex if and only if”
GENERALIZED ADDITIVE PARTIAL LINEAR MODELS WITH HIGH-DIMENSIONAL COVARIATES (2013, background): “Yatchew (2003) is an excellent account of semiparametric regression with an emphasis on empirical applications.”
Restricted Ridge Estimators of the Parameters in Semiparametric Regression Model (2009, unknown): “…is Fdf1 df2 ≈ ( R̃ − r)′(Rvar(̃)R′)−1(R̃ − r) RSS/tr I −Hs ′ I −Hs = 0 000461 with degrees of freedom v1 = df1 = rank R and v2 = df2 = tr I −Hs ′ I −Hs = 83 8210, where Hs = S + X̃ X̃′X̃ −1X̃′ I − S and the residual sum of squares RSS = I −Hs y 2 (see Schimek, 2000, p. 532; Yatchew, 2003, p. 72).”