Partial effects in non-linear panel data models with correlated random effects [0.03%]
具有相关随机效应的非线性面板数据模型中的部分效应
Jason Abrevaya,Yu-Chin Hsu
Jason Abrevaya
Nonlinearity and heterogeneity are known to cause difficulties in estimating and interpreting partial effects. This paper provides a systematic characterization of the various partial effects in nonlinear panel data models that might be of ...
Molei Liu,Y I Zhang,Doudou Zhou
Molei Liu
We propose double/debiased machine learning approaches to infer a parametric component of a logistic partially linear model. Our framework is based on a Neyman orthogonal score equation consisting of two nuisance models for the nonparametri...
Using a Satisficing Model of Experimenter Decision-Making to Guide Finite-Sample Inference for Compromised Experiments [0.03%]
使用满足模型来指导妥协实验的有限样本推断决策制定
James J Heckman,Ganesh Karapakula
James J Heckman
This paper presents a simple decision-theoretic economic approach for analyzing social experiments with compromised random assignment protocols that are only partially documented. We model administratively constrained experimenters who sati...
Model averaging estimation for high-dimensional covariance matrices with a network structure [0.03%]
具有网络结构的高维协方差矩阵的模型平均估计方法
Rong Zhu,Xinyu Zhang,Yanyuan Ma et al.
Rong Zhu et al.
In this paper, we develop a model averaging method to estimate a high-dimensional covariance matrix, where the candidate models are constructed by different orders of polynomial functions. We propose a Mallows-type model averaging criterion...
Peer effects in bedtime decisions among adolescents: a social network model with sampled data [0.03%]
青少年就寝决定中的同伴效应：基于抽样数据的社交网络模型
Xiaodong Liu,Eleonora Patacchini,Edoardo Rainone
Xiaodong Liu
Using unique information on a representative sample of US teenagers, we investigate peer effects in adolescent bedtime decisions. We extend the nonlinear least-squares estimator for spatial autoregressive models to estimate network models w...
My friend far, far away: a random field approach to exponential random graph models [0.03%]
远在天边的朋友：指数随机图模型的随机域方法
Vincent Boucher,Ismael Mourifié
Vincent Boucher
We explore the asymptotic properties of strategic models of network formation in very large populations. Specifically, we focus on (undirected) exponential random graph models. We want to recover a set of parameters from the individuals' ut...
Rebecca Allen,Simon Burgess,Russell Davidson et al.
Rebecca Allen et al.
The most widely used measure of segregation is the so-called dissimilarity index. It is now well understood that this measure also reflects randomness in the allocation of individuals to units (i.e. it measures deviations from evenness, not...
Andrew Chesher,Adam M Rosen
Andrew Chesher
In this paper, we study a random-coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. ...
A Note on Adapting Propensity Score Matching and Selection Models to Choice Based Samples [0.03%]
关于适应选择基础样本的倾向值匹配和选择模型的注记
James J Heckman,Petra E Todd
James J Heckman