Showing 1 - 6 of 6
approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In this paper we … focus on the latter and consider both univariate and multivariate panel data models with short time dimension. Simple Bias …
Persistent link: https://www.econbiz.de/10012943450
This paper considers estimation and inference in fixed effects (FE) panel regression models with lagged dependent … generalization of the Nickell type bias derived in the literature for the pure dynamic panel data models. It shows that in the … sufficiently small. To deal with the bias and size distortion of FE estimator when NN is large relative to TT, the use of half-panel …
Persistent link: https://www.econbiz.de/10012968220
This paper extends the mean group (MG) estimator for random coefficient panel data models by allowing the underlying …
Persistent link: https://www.econbiz.de/10012850844
-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution … crosssection dimension (N) are both large. The CS-DL approach is compared with more standard panel data estimators that are based … is often superior to the alternative panel ARDL estimates particularly when T is not too large and lies in the range of …
Persistent link: https://www.econbiz.de/10012971242
This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable),...
Persistent link: https://www.econbiz.de/10012849494
We compare the finite sample performance of a variety of consistent approaches to estimating Impulse Response Functions (IRFs) in a linear setup when the shock of interest is observed. Although there is no uniformly superior approach, iterated approaches turn out to perform well in terms of root...
Persistent link: https://www.econbiz.de/10012849624