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A quantile correlated random coefficients panel data model
Graham, Bryan S.; Hahn, Jinyong; Poirier, Alexandre; … - 2016
We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...
Persistent link: https://www.econbiz.de/10011524832
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Quantile regression with panel data
Graham, Bryan S.; Hahn, Jinyong; Poirier, Alexandre; … - 2015
We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...
Persistent link: https://www.econbiz.de/10010494997
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Kernel density estimation for undirected dyadic data
Graham, Bryan S.; Niu, Fengshi; Powell, James - 2019 - This Draft: July 2019
We study nonparametric estimation of density functions for undirected dyadic random variables (i.e., random variables … kernel estimation method of Rosenblatt (1956) and Parzen (1962). We suggest an estimate of their asymptotic variances … inspired by a combination of (i) Newey’s (1994) method of variance estimation for kernel estimators in the “monadic” setting …
Persistent link: https://www.econbiz.de/10012053034
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Semiparametrically efficient estimation of the average linear regression function
Graham, Bryan S.; Pinto, Cristine Campos de Xavier - 2018
Let Y be an outcome of interest, X a vector of treatment measures, and W a vector of pre-treatment control variables. Here X may include (combinations of) continuous, discrete, and/or non-mutually exclusive "treatments". Consider the linear regression of Y onto X in a subpopulation homogenous in...
Persistent link: https://www.econbiz.de/10011924562
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Minimax risk and uniform convergence rates for nonparametric dyadic regression
Graham, Bryan S.; Niu, Fengshi; Powell, James - 2021 - This Draft: March 2021
Let i = 1, . . . , N index a simple random sample of units drawn from some large population. For each unit we observe the vector of regressors Xi and, for each of the N (N - 1) ordered pairs of units, an outcome Yij . The outcomes Yij and Ykl are independent if their indices are disjoint, but...
Persistent link: https://www.econbiz.de/10012482913
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An econometric model of network formation with degree heterogeneity
Graham, Bryan S. - 2017 - This draft: December 2016
I introduce a model of undirected dyadic link formation which allows for assortative matching on observed agent characteristics (homophily) as well as unrestricted agent level heterogeneity in link surplus (degree heterogeneity). Like in fixed effects panel data analyses, the joint distribution...
Persistent link: https://www.econbiz.de/10011596621
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Identification in a binary choice panel data model with a predetermined covariate
Bonhomme, Stéphane; Dano, Kevin; Graham, Bryan S. - 2023
We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter θ, whereas the distribution of unit-specific...
Persistent link: https://www.econbiz.de/10014316769
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Sparse network asymptotics for logistic regression under possible misspecification
Graham, Bryan S. - 2022 - This Draft: September 2022
pseudo-true parameter under general misspecification. With respect to sampling theory, sparseness implies that the first and …
Persistent link: https://www.econbiz.de/10013387359
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Identification in a binary choice panel data model with a predetermined covariate
Bonhomme, Stéphane; Dano, Kevin; Graham, Bryan S. - 2023
We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter θ, whereas the distribution of unit-specific...
Persistent link: https://www.econbiz.de/10013489540
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Identification and efficiency bounds for the average match function under conditionally exogenous matching
Graham, Bryan S.; Imbens, Guido; Ridder, Geert - 2016
Consider two heterogenous populations of agents who, when matched, jointly produce an output, Y. For example, teachers and classrooms of students together produce achievement, parents raise children, whose life outcomes vary in adulthood, assembly plant managers and workers produce a certain...
Persistent link: https://www.econbiz.de/10011440476