Dear all,
when calculating a linear regression with panel data (xtpcse) I get the message that my sample contains gaps. The option "detail" tells me about 2 "observations with preceding time gaps" (see below). Looking at the data cannot see why there should be any time gaps, there are observations for the years before and the following year. Do you have any idea why stata identifies these gaps and how I can correct them?
Thanks in advance.
Best regards
Sebastian
Number of gaps in sample: 2
Observations with preceding time gaps
----------------------------------
Record | Country Year
----------+-----------------------
278 | Germany 2004
323 | Hungary 2005
----------------------------------
Linear regression, correlated panels corrected standard errors (PCSEs)
Group variable: cnt Number of obs = 121
Time variable: year Number of groups = 16
Panels: correlated (unbalanced) Obs per group: min = 3
Autocorrelation: no autocorrelation avg = 7.5625
Sigma computed by pairwise selection max = 11
Estimated covariances = 136 R-squared = 0.3147
Estimated autocorrelations = 0 Wald chi2(18) = 52.43
Estimated coefficients = 26 Prob > chi2 = 0.0000
when calculating a linear regression with panel data (xtpcse) I get the message that my sample contains gaps. The option "detail" tells me about 2 "observations with preceding time gaps" (see below). Looking at the data cannot see why there should be any time gaps, there are observations for the years before and the following year. Do you have any idea why stata identifies these gaps and how I can correct them?
Thanks in advance.
Best regards
Sebastian
Number of gaps in sample: 2
Observations with preceding time gaps
----------------------------------
Record | Country Year
----------+-----------------------
278 | Germany 2004
323 | Hungary 2005
----------------------------------
Linear regression, correlated panels corrected standard errors (PCSEs)
Group variable: cnt Number of obs = 121
Time variable: year Number of groups = 16
Panels: correlated (unbalanced) Obs per group: min = 3
Autocorrelation: no autocorrelation avg = 7.5625
Sigma computed by pairwise selection max = 11
Estimated covariances = 136 R-squared = 0.3147
Estimated autocorrelations = 0 Wald chi2(18) = 52.43
Estimated coefficients = 26 Prob > chi2 = 0.0000
