14 citations · 18 across the 14 of their papers we have counts for
16 papers
GMM for Panel Data Quantile Regression
Antonio F. Galvao, Ulrich Hounyo, Jiahao Lin
This paper develops a smoothed generalized method of moments (GMM) framework for panel quantile models with individual-specific fixed-effects and endogenous regressors. By smoothin…
Bootstrap Inference with a Randomly Assigned Regressor: Covariance Filtering and the Limits of Marginal Resampling
Ulrich Hounyo, Jungbin Hwang
Random assignment can make ordinary least squares (OLS) inference insensitive to outcome dependence, yet iid resampling can still fail because assignment and resampling need not re…
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…
Distributional Difference-in-Differences: Aggregation Before or After Quantile Inversion?
Ulrich Hounyo
Staggered distributional difference-in-differences produces cohort-specific potential-outcome distributions, but applied work typically wants one overall quantile treatment effect.…
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 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…
Adaptive Econometric Inference under Unknown Dependence: Contrast-Local Validity
Ulrich Hounyo
Empirical conclusions can depend on how researchers model dependence when constructing standard errors. We develop contrast-local validity, which asks whether a covariance restrict…
Bootstrap Inference under General Two-way Clustering with Serially and Spatially Dependent Common Effects
Ulrich Hounyo, Jiahao Lin
This paper develops bootstrap procedures for inference in linear regression models with two-way clustered data. We characterize the estimator's asymptotic behavior in five mutually…
Two-way Clustering Robust Variance Estimator in Quantile Regression Models
Ulrich Hounyo, Jiahao Lin
We study inference for linear quantile regression with two-way clustered data. Using a separately exchangeable array framework and a projection decomposition of the quantile score,…
Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment
Kim Christensen, Ulrich Hounyo, Mark Podolskij
In this paper, we propose a nonparametric way to test the hypothesis that time-variation in intraday volatility is caused solely by a deterministic and recurrent diurnal pattern. W…
Robust Two-Sample Inference under Serial Dependence
Ulrich Hounyo, Min Seong Kim
We propose robust inference for two-sample comparison with time-series data under serial dependence and heterogeneous long-run variances. Standardizing with orthonormal-basis (seri…
A nonparametric test for diurnal variation in spot correlation processes
Kim Christensen, Ulrich Hounyo, Zhi Liu
The association between log-price increments of exchange-traded equities, as measured by their spot correlation estimated from high-frequency data, exhibits a pronounced upward-slo…
The Local Fractional Bootstrap
Mikkel Bennedsen, Ulrich Hounyo, Asger Lunde +1
We introduce a bootstrap procedure for high-frequency statistics of Brownian semistationary processes. More specifically, we focus on a hypothesis test on the roughness of sample p…