The empirical model is estimated using the fixed-effects estimator with Driscoll-Kraay standard errors. The findings indicate the existence of a significant positive relation between fintech development and renewable energy use. The results provide a platform for governments and policymakers to promote ...
To assess the similarity of the populations before and after the intervention, we examined characteristics before and after the intervention (eTable 3 in Supplement 1).We report the results from both 2-way fixed-effects estimators and doubly robust estimators in which only not-yet-treated groups ...
Options for FE model £ £ Model fe requests the fixed-effects estimator. exposure(varname), offset(varname), constraints(constraints); see [R] Estimation options. £ £ SE/Robust vce(vcetype) specifies the type of standard error reported, which includes types that ...
estimatorFixedeffectsHeteroscedasticerrorsIncidentalparameterPartiallylinearFixed effects panel data regression models are useYouShanghai You,Jinhong,Hu,... - 《Journal of Multivariate Analysis An International Journal》 被引量: 0发表: 2017年 加载更多来源...
As well, using fixed effects model won't > be able to observe time-invariant variables. > > My question is, is it necessary to perform another Hausman > Test to state again that the Hausman-Taylor is a consistent estimator? > > However, I actually conducted the Hausman Test and found ...
The RDS-II estimator assumes that: 1. Respondents are members of a completely connected network with a finite (but large) population size; 2. Recruitment ties are reciprocal; 3. Respondents can accurately report their degree; 4. Respondents recruit those from their personal network at random; 5...
But it works: for any number of endogenous regressors, with/without fixed-effects. Of course you have to adapt many things but I think it can be used as a good starting point. I hope you'll enjoy the package and that the previous code will help!
The inverse variance heterogeneity (IVH) model was chosen for meta-analysis results because it is an estimator model that uses a fixed effects model assumption that has a quasi–likelihood-based variance structure, which is considered more robust than other models.108 In contrast, the random ...
Abbas Q, Nurunnabi M, Alfakhri Y, Khan W, Hussain A, Iqbal W (2020) The role of fixed capital formation, renewable and non-renewable energy in economic growth and carbon emission: a case study of Belt and Road Initiative project. Environ Sci Pollut Res 27(36):45476–45486 Article Googl...
To leverage more of our data, we next considered panel data models as a means to address unobserved variables. We consider both within-estimator models (also known as “fixed effects” in causal inference terminology, but different from the biostatistical use of the term) and random effects mode...