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From the 1 of 12 linked papers with an AI index.

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12 papers

econ.EM2026

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…

econ.EM2026

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…

econ.EM2026

Specification Testing for Dyadic Regression Models

Ulrich Hounyo, Jiahao Lin, Xiaojun Song

The paper proposes omnibus specification tests for linear conditional‑mean models with undirected dyadic data, introducing a corrected Gaussian bootstrap and Kolmogorov‑Smirnov and…

econ.EM2026

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,…

econ.EM2026

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…

econ.EM2026

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…