I understand the basic differences between a fixed-effects and a random-effects model for a panel dataset, but what is the “between estimator”? The manual explains the command, but I cannot figure out what would lead one to choose (or not choose) the between estimator. ...
between-estimator Star Here is 1 public repository matching this topic... Additional linear models including instrumental variable and panel data models that are missing from statsmodels. panelregressionolsgmmivlinear-modelsasset-pricingpanel-datafixed-effectsrandom-effectsinstrumental-variablestatistical-model...
I understand the basic differences between a fixed-effects and a random-effects model for a panel dataset, but what is the "between estimator"? The manual explains the command, but I cannot figure out what would lead one to choose (or not choose) the between estimator. ...
I apply several common panel data estimators including the between estimator to OECD and global carbon and sulfur emissions datasets. The between estimates of the sulfur-income elasticity are 0.732 in the OECD and 1.067 in the global data set and the estimated carbon-income elasticity is 1.612 in...
Predicting the evolution of a large system of units using its structure of interaction is a fundamental problem in complex system theory. And so is the problem of reconstructing the structure of interaction from temporal observations. Here, we find an in
Predicting the evolution of a large system of units using its structure of interaction is a fundamental problem in complex system theory. And so is the problem of reconstructing the structure of interaction from temporal observations. Here, we find an in
panel data analysis since the dependent variable is not completely exogenous (Ditzen2019). Moreover, unlike other methods, the DCCE method uses additional lags of cross-sectional units to solve the CSD problem. It solves the heterogeneity problem based on the properties of the MG estimator and ...
The methodology used in the study is the Panel Autoregressive-Distributed Lag (ARDL) model estimates using pooled mean group (PMG) estimator and the results show a statistically significant and positive effect of increase in fixed broadband subscriptions and internet connections on economic growth. ...
panel data analysis since the dependent variable is not completely exogenous (Ditzen2019). Moreover, unlike other methods, the DCCE method uses additional lags of cross-sectional units to solve the CSD problem. It solves the heterogeneity problem based on the properties of the MG estimator and ...
: A pretest estimator This paper suggests a pretest estimator based upon two Hausman tests as an alternative to the fixed effects or random effects estimators for panel data mod... Badi,H.,Baltagi,... - 《Economics Letters》 被引量: 417发表: 2003年 Fixed effects, random effects or Hausman...