14 citations · 14 across the 9 of their papers we have counts for
12 papers
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…
Supervised Mixed-Frequency Learning for Macro-Financial Forecasting When Factors are Weak
Ulrich Hounyo, Zhendong Li
Factor-MIDAS regressions forecast a low-frequency target by extracting common factors from a large panel of high-frequency predictors via principal component analysis (PCA). While…
Identification and Information after Nuisance Projection
Ulrich Hounyo
Empirical work often removes fixed effects, latent factors, or high-dimensional controls before estimating structural relationships. These transformations reduce confounding but ma…
When Does Heteroskedasticity Matter? A Contrast-Specific Theory of Robust Inference
Ulrich Hounyo
Conventional heteroskedasticity diagnostics ask whether the conditional variance of the regression disturbance varies with covariates. This paper asks a different question: when do…
Estimation and Inference for the -Quantile of Individual Heterogeneous Coefficient
Antonio F. Galvao, Ulrich Hounyo, Jiahao Lin
This paper proposes estimation and inference procedures for quantiles of the heterogeneous individual-specific coefficients in panel data. Unlike conventional panel quantile regres…
Robust Inference for Dyadic Data with Dependent Ordered Nodes
Ulrich Hounyo, Jiahao Lin, Xiaojun Song
Dyadic regression models are commonly analyzed under the conventional dyadic dependence framework, where two observations may be dependent only if the corresponding dyads share a n…