Zobrazeno 1 - 10
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pro vyhledávání: '"Webb, Matthew"'
Autor:
Niculescu, Gabriela E., Bejger, Gerald R., Barber, John P., Wright, Joshua T., Almishal, Saeed S. I., Webb, Matthew, Ayyagari, Sai Venkata Gayathri, Maria, Jon-Paul, Alem, Nasim, Heron, John T., Rost, Christina M.
High entropy oxides (HEO)s have garnered much interest due to their available high degree of tunability. Here, we study the local structure of (MgNiCuCoZn)0.167(MnCr)0.083O, a composition based on the parent HEO (MgNiCuCoZn)0.2O.We synthesized a seri
Externí odkaz:
http://arxiv.org/abs/2406.13550
For linear regression models with cross-section or panel data, it is natural to assume that the disturbances are clustered in two dimensions. However, the finite-sample properties of two-way cluster-robust tests and confidence intervals are often poo
Externí odkaz:
http://arxiv.org/abs/2406.08880
We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but als
Externí odkaz:
http://arxiv.org/abs/2406.00650
This paper details an innovative methodology to integrate image data into traditional econometric models. Motivated by forecasting sales prices for residential real estate, we harness the power of deep learning to add "information" contained in image
Externí odkaz:
http://arxiv.org/abs/2403.19915
Difference-in-differences (DID) is commonly used to estimate treatment effects but is infeasible in settings where data are unpoolable due to privacy concerns or legal restrictions on data sharing, particularly across jurisdictions. In this study, we
Externí odkaz:
http://arxiv.org/abs/2403.15910
We provide computationally attractive methods to obtain jackknife-based cluster-robust variance matrix estimators (CRVEs) for linear regression models estimated by least squares. We also propose several new variants of the wild cluster bootstrap, whi
Externí odkaz:
http://arxiv.org/abs/2301.04527
The overwhelming majority of empirical research that uses cluster-robust inference assumes that the clustering structure is known, even though there are often several possible ways in which a dataset could be clustered. We propose two tests for the c
Externí odkaz:
http://arxiv.org/abs/2301.04522
We introduce a new Stata package called summclust that summarizes the cluster structure of the dataset for linear regression models with clustered disturbances. The key unit of observation for such a model is the cluster. We therefore propose cluster
Externí odkaz:
http://arxiv.org/abs/2205.03288