Showing 1 - 10 of 1,062
Persistent link: https://www.econbiz.de/10001526715
A growing literature on inference in difference-in-differences (DiD) designs with grouped errors has been pessimistic about obtaining hypothesis tests of the correct size, particularly with few groups. We provide Monte Carlo evidence for three points: (i) it is possible to obtain tests of the...
Persistent link: https://www.econbiz.de/10010221878
We study the finite sample behavior of Lasso-based inference methods such as post double Lasso and debiased Lasso. Empirically and theoretically, we show that these methods can exhibit substantial omitted variable biases (OVBs) due to Lasso not selecting relevant controls. This phenomenon can be...
Persistent link: https://www.econbiz.de/10012849415
Persistent link: https://www.econbiz.de/10012388217
This paper revisits the issue of environment and development raised in the 1992 World Development Report, with new analysis tools and data. The paper discusses inference and interpretation in a machine learning framework. The results suggest that production gradually favors conserving the...
Persistent link: https://www.econbiz.de/10012008015
Persistent link: https://www.econbiz.de/10011945845
This paper considers estimation and inference concerning the autoregressive coefficient (p) in a panel autoregression for which the degree of persistence in the time dimension is unknown. Our main objective is to construct confidence intervals for p that are asymptotically valid, having...
Persistent link: https://www.econbiz.de/10012160749
The main contribution of this paper is to add to the literature by suggesting a dynamic OLS (DOLS) estimator and providing a serious comparison of the finite sample properties of the OLS, fully modified OLS (FMOLS), and DOLS estimators in panel cointegrated regression models. Monte Carlo results...
Persistent link: https://www.econbiz.de/10013127238
In this paper, we study the asymptotic distributions for least-squares (OLS), fully modified (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic...
Persistent link: https://www.econbiz.de/10014149909
In this paper we propose a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the...
Persistent link: https://www.econbiz.de/10003878985