I have a data frame with the variables Judge ID (uniquely identifies judges), Case ID (uniquely identifies court cases), Decision (records case outcome), and Comp Date (variable specifying case completion date). Below, I have provided a table to illustrate what this data might look like for a set of four judges between August 27 and August 30, 2009:
Each observation in the dataset corresponds to a unique case. Some judges oversee more cases than others, and case completion date is random across judges. Is this an unbalanced panel dataset? I read that unbalanced panel data is defined as when at least one panel unit (e.g. a judge) is not observed every period. However, in this dataset, a judge may go many days without completing a case. In addition, it is common for a judge to complete more than one case on the same day. If this data frame is not unbalanced panel data, what type of statistical data is it? Can I only analyze it as cross-sectional data?
| Judge_ID | Case_ID | Decision | Comp_Date |
| XDF | 1993 | Conviction | 27aug2009 |
| XDF | 2047 | Relief | 27aug2009 |
| XDF | 893 | Conviction | 30aug2009 |
| JCF | 431 | Conviction | 27aug2009 |
| XYQ | 4449 | Conviction | 28aug2009 |
| XYQ | 8481 | Conviction | 28aug2009 |
| XYQ | 2199 | Relief | 28aug2009 |
| TBX | 7832 | Relief | 27aug2009 |
Each observation in the dataset corresponds to a unique case. Some judges oversee more cases than others, and case completion date is random across judges. Is this an unbalanced panel dataset? I read that unbalanced panel data is defined as when at least one panel unit (e.g. a judge) is not observed every period. However, in this dataset, a judge may go many days without completing a case. In addition, it is common for a judge to complete more than one case on the same day. If this data frame is not unbalanced panel data, what type of statistical data is it? Can I only analyze it as cross-sectional data?