1 citations · 1 across the 12 of their papers we have counts for
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Specification Testing for Dyadic Regression Models
Ulrich Hounyo, Jiahao Lin, Xiaojun Song
This paper develops omnibus specification tests for linear conditional-mean models with undirected dyadic data. We establish a uniform projection theorem that reduces the dyadic pr…
Robust Inference for Dyadic Data with Spatially Dependent Nodes
Ulrich Hounyo, Jiahao Lin, Xiaojun Song
We develop inference for complete dyadic samples with spatial dependence governed by geographic distances between nodes, covering settings beyond the scope of existing dyadic infer…
Testing Heteroskedasticity Under Measurement Error
Xiaojun Song, Jichao Yuan
In this paper, we propose a novel approach to detect heteroskedasticity in regression models with regressors contaminated by measurement error. Specifically, inspired by the integr…
Nonparametric Tests of Conditional Independence for Time Series
Xiaojun Song, Haoyu Wei
We propose consistent nonparametric tests of conditional independence for time series data. Our methods are motivated from the difference between joint conditional cumulative distr…
Data-driven Smooth Tests for Normality in ANOVA When the Number of Groups is Large
Peiwen Jia, Xiaojun Song, Haoyu Wei
The normality assumption for random errors is fundamental in the analysis of variance (ANOVA) models. However, it is rarely subjected to formal testing in practice, and theoretical…
Specification tests for generalized propensity scores using double projections
Pedro H. C. Sant'Anna, Xiaojun Song
This paper proposes a new class of nonparametric tests for the correct specification of models based on conditional moment restrictions, paying particular attention to generalized…
Covariate Distribution Balance via Propensity Scores
Pedro H. C. Sant'Anna, Xiaojun Song, Qi Xu
This paper proposes new estimators for the propensity score that aim to maximize the covariate distribution balance among different treatment groups. Heuristically, our proposed pr…