De Luca, G. (2008). SNP and SML estimation of univariate and bivariate binary-choice models. Stata Journal, 8: 190-220.
De Luca, G., and Magnus, J. R. (2011). Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues. Stata Journal, 11: 518-544.
De Luca, G., and Perotti, V. (2011). Estimation of ordered response models with sample selection. Stata Journal, 11: 213-239.
Dardanoni, V., De Luca, G., Modica, S., and Peracchi, F. (2012). A generalized missing-indicator approach to regression with imputed covariates. Stata Journal, 12: 575-604.
De Luca, G., and Peracchi, F. (2012). Estimating Engel curves under unit and item nonresponse. Journal of Applied Econometrics, 27: 1076-1099.
De Luca, G., Rossetti, C., and Vuri, D. (2014). In-work benefits for married couples: an ex-ante evaluation of EITC and WTC policies in Italy. IZA Journal of Labor Policy, 3: 23.
Dardanoni, V., De Luca, G., Modica, S., and Peracchi, F. (2015). Model averaging estimation of generalized linear models with imputed covariates. Journal of Econometrics, 184: 452-463.
Magnus, J. R., and De Luca, G. (2016). Weighted-average least squares (WALS): A survey. Journal of Economic Surveys, 30: 117-148.
De Luca, G., Magnus, J. R., and Peracchi, F. (2018). Weighted-average least squares estimation of generalized linear models. Journal of Econometrics, 204: 1-17.
De Luca, G., Magnus, J. R., and Peracchi, F. (2018). Balanced variable addition in linear models. Journal of Economic Surveys, 32: 1183-1200.
De Luca, G., Magnus, J. R., and Peracchi, F. (2019). Comments on “Unobservable Selection and Coefficient Stability: Theory and Evidence” and “Poorly Measured Confounders are More Useful on the Left Than on the Right”. Journal of Business & Economic Statistics, 37: 217-222.
De Luca, G., Magnus, J. R., and Peracchi, F. (2021). Posterior moments and quantiles for the normal location model with Laplace prior. Communications in Statistics Theory and Methods, 50(17), 4039-4049.
De Luca, G., and Magnus, J. R. (2021). Weak versus strong dominance of shrinkage estimators. Journal of Quantitative Economics, 19, 239-266.
De Luca, G., Magnus, J. R., and Peracchi, F. (2022). Sampling properties of the Bayesian posterior mean with an application to WALS estimation. Journal of Econometrics, 230, 299-317.
De Luca, G., Magnus, J. R., and Peracchi, F. (2023). Weighted-average least squares (WALS): Confidence and prediction intervals. Computational Economics, 61, 1637-1664.
De Luca, G., and Magnus, J. R. (2024). Shrinkage efficiency bounds: An extension. Communications in Statistics Theory and Methods, 53(11), 4147-4152.
De Luca, G., Magnus, J. R., and Peracchi, F. (2025). Bayesian estimation of the normal location model: A non-standard approach. Oxford Bulletin of Economics and Statistics, 87, 913-923.
De Luca, G., Magnus, J. R., and Vasnev, A. L. (2025). Maximum likelihood estimation of the linear model with equicorrelated errors. Communications in Statistics - Theory and Methods, 54, 6295-6302.
De Luca, G., and Magnus, J. R. (2025b). Weighted-average least squares: improvements and extensions. The Stata Journal, 25(3), 587-626.
De Luca, G. and Magnus, J. R. (2025c). Weighted-average least squares: Beyond the simple linear regression model. The Stata Journal, 25(4), 1-40.