Hello,

I’m analyzing the probability that individuals employed in a certain industry will transition to employment in every other industry by matching individuals’ CPS BMS responses across each month that they are in the survey (i.e. up to 8 ‘waves’, for mish=1,…,8). I have constructed the dataset such that I now have observations for each individual and a series of variables origin_wave and destination_wave that record the value of variable mish for whichever monthly survey wave they last reported employment in my industry of interest (=1, 2, …7) as well as the next monthly survey wave that they reported employment in a different industry (=2, 3, …, 8), respectively. So for example I have data that looks like:

```
+---------------------------------------------------------------+
| cpsidp origin_wave destination_wave destination_ind|
|---------------------------------------------------------------|
13. | 2.00001e+13 7 8 250 |
69. | 2.00001e+13 1 2 241 |
77. | 2.00001e+13 4 5 522 |
93. | 2.00001e+13 1 4 321 |
165. | 2.00001e+13 3 7 180 |
```

I now want to combine all these transitions into a single calculation of the probability of transitioning to each industry. What are the appropriate weights to use when combining all these transitions into a single calculation? In particular, can I mix together the different weights described in the documentation as follows: for each individual’s transition I assign a weight that depends on which of their monthly waves are in the values of origin_wave and destination_wave:

- if adjacent months (at any point, e.g. mish=1 and 2; 5 and 6; or 6 and 7, etc) → use lnkfw1mwt
- if not adjacent months but both are within the first 4 months of the panel rotation (mish 1-4) → use lnkfwmis14wt
- if not adjacent but both are within the last 4 months of the panel rotation (mish 5-8) → use lnkfwmis58wt
- if any two months across the break (i.e. mish1-4 and 5-8) → use lnkfwmis45wt

Is this approach correct, or is there something else that would be better?

Thank you in advance for your help!