sparsity of the spatial weights matrix. The proposed estimation methodology exploits the Lasso estimator and mimics two …-stage least squares (2SLS) to account for endogeneity of the spatial lag. The developed two-step estimator is of more general … larger than the number of observations. We derive convergence rates for the two-step Lasso estimator. Our Monte Carlo …

approximate sparsity of the spatial weights matrix. The proposed estimation methodology exploits the Lasso estimator and mimics … two-stage least squares (2SLS) to account for endogeneity of the spatial lag. The developed two-step estimator is of more … variables is larger than the number of observations. We derive convergence rates for the two-step Lasso estimator. Our Monte …

coefficients, and the number of breaks and their locations by applying a version of the Lasso approach. We show that with …

units (“donors pool”) using shrinkage methods, such as the Least Absolute Shrinkage Operator (LASSO). In the second stage …

units ("donors pool") using shrinkage methods, such as the Least Absolute Shrinkage Operator (LASSO). In the second stage …