Description
Label an explicitly assigned observation cluster and clustering dimension.
Econometric calculations separate supplied residuals, regressors, weights, restrictions, panel groups and reference periods. One score or moment contribution is not a fitted estimator, and one scalar covariance term is not a standard error. Unit rescaling and event-time arithmetic preserve conventions without establishing model identification or causal interpretation.
Label an explicitly assigned observation cluster and clustering dimension.
When to use this tool
Use Cluster Membership Label when you already have observationCode, clusterCode, clusterDimension and need to label an explicitly assigned observation cluster and clustering dimension.
How to use the tool and how it works
- Enter observationCode, clusterCode, clusterDimension. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read label. Use the output convention below.
Enter observationCode, clusterDimension, clusterCode using the field constraints below. Encode these values, in exactly that order, as a JSON array and return the serialized array as text in label. String values are preserved without trimming or external terminology lookup.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| observationCode | Observation Code | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192. |
| clusterCode | Cluster Code | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192. |
| clusterDimension | Cluster Dimension | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| label | Label | Required. Text; maximum UTF-16 length 8192. |
{
"input": {
"observationCode": "O17",
"clusterCode": "F3",
"clusterDimension": "firm"
},
"output": {
"label": "[\"O17\",\"firm\",\"F3\"]"
}
}Limitations and assumptions
- The result records supplied values without selecting standard-error assumptions. Sources and asserted relationships are not independently authenticated.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
Alternative or Complementary methods
Fit and evaluate the full specified model with appropriate data, grouping and uncertainty treatment for inference. Aggregate the required score/moment terms and use the complete covariance calculation; a local residual, cutoff flag or supplied coefficient transformation does not validate the estimator.
References
Similar or alternative tools
- Event Study Omitted Period Label
Record an explicit event-study omitted period and convention.
- Clustered Score Single Observation Contribution
Label one supplied regression-score contribution by cluster.