Contents
Is there Heteroskedasticity in panel data?
In the research, both autocorrelation and heteroskedasticity are detected in panel data analysis.
What is cross-sectional dependence in panel data?
Panel data can be subject to pervasive cross-sectional dependence, whereby all units in the same cross-section are correlated. This is usually attributed to the effect of some unobserved common factors, common to all units and affecting each of them, although possibly in different ways.
What is cross sectional survey method?
A cross-sectional survey collects data to make inferences about a population of interest (universe) at one point in time. Cross-sectional surveys have been described as snapshots of the populations about which they gather data. Panel surveys usually are conducted to measure change in the population being studied.
How to deal with Heteroskedasticity and cross sectional dependence?
To deal with heteroskedasticity I use a classic Robust Covariance Matrix (function vcovHC, specifically method arellano). Obviously, both methods result in different SE. Is there a way how to account for both heteroskedasticity and cross-sectional dependence at the same time?
How to solve cross sectional dependence and serial dependence?
For cross sectional dependence use spatial approach or factor structural approach. For details go through the paper “Cross-sectional Dependence in Panel Data Analysis”. Hie Nosheen.
Which is the best cross sectional Dependence Estimator?
To deal with a cross-sectional dependence I use a Driscoll And Kraay (1998) Robust Covariance Matrix Estimator (function vcovSCC in R). To deal with heteroskedasticity I use a classic Robust Covariance Matrix (function vcovHC, specifically method arellano). Obviously, both methods result in different SE.
How to deal with serial correlation in panel data model?
For dealing with serial correlation in panel data model, the most straighforward tool is to cluster the standard errors at the unit level. This is readily available in most of the statistical softwares (e.g., Stata). It is a conservative strategy, as your errors would be robust to all sort of serial correlation.