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## Why does my merge produce a dataset with too many observations?

 Title Match merging when there are duplicate IDs Author William Gould, StataCorp

Your problem is most likely caused by having duplicate IDs. Duplicate IDs can cause unexpected results when doing a match merge. Consider the following examples:

### Example 1. There are too many observations in the merged dataset

The master dataset has 5 observations, and the using dataset has 8 observations. When you do the merge, every observation has a _merge code of 2 or 3 (every observation in the master dataset was matched), yet the merged dataset contains 9 observations.

Cause: Duplicate observations in the smaller dataset (and perhaps in the larger one, too).

. use junk2  [this is the "using" dataset]

. list

+--------+
| id   y |
|--------|
1. |  1   1 |
2. |  1   2 |
3. |  1   3 |
4. |  2   1 |
5. |  3   1 |
|--------|
6. |  3   2 |
7. |  4   1 |
8. |  5   1 |
+--------+

. use junk1, clear  [this is the master dataset]

. sort id x

. list

+--------+
| id   x |
|--------|
1. |  1   1 |
2. |  1   2 |
3. |  2   1 |
4. |  2   2 |
5. |  3   1 |
+--------+

. merge id using junk2
variable id does not uniquely identify observations in the master data
variable id does not uniquely identify observations in junk2.dta

. list

+---------------------+
| id   x   y   _merge |
|---------------------|
1. |  1   1   1        3 |
2. |  1   2   2        3 |
3. |  2   1   1        3 |
4. |  2   2   1        3 |
5. |  3   1   1        3 |
|---------------------|
6. |  1   2   3        3 |
7. |  3   1   2        3 |
8. |  4   .   1        2 |
9. |  5   .   1        2 |
+---------------------+


Examine x and y, and you will see how merge matches up duplicates.

### Example 2. More matches than observations in the smallest dataset

There are only 3 observations in your master dataset, yet, when you do the merge, there are 4 observations that have a _merge code of 3 (meaning the observations are in both datasets).

Cause: There are duplicates in the using dataset.

. use junk2, clear  [this is the "using" dataset]

. list

+--------+
| id   y |
|--------|
1. |  1   1 |
2. |  1   2 |
3. |  1   3 |
4. |  2   1 |
5. |  3   1 |
|--------|
6. |  3   2 |
7. |  4   1 |
8. |  5   1 |
+--------+

. use junk1, clear  [this is the master dataset]

. sort id x

. list

+--------+
| id   x |
|--------|
1. |  1   1 |
2. |  2   2 |
3. |  3   3 |
+--------+

. merge id using junk2
variable id does not uniquely identify observations in junk2.dta

.  list

+---------------------+
| id   x   y   _merge |
|---------------------|
1. |  1   1   1        3 |
2. |  2   2   1        3 |
3. |  3   3   1        3 |
4. |  1   1   2        3 |
5. |  1   1   3        3 |
|---------------------|
6. |  3   3   2        3 |
7. |  4   .   1        2 |
8. |  5   .   1        2 |
+---------------------+


### Finding duplicate IDs

The duplicates and isid commands help identify and deal with duplicate observations.