**EDIT #1**

Most likely I have set up the function `bic.mlogit` in a wrong way. @Jesper Hybel, hopefully, directed me in the right way. With the new setup I get two sets of coefficients for both of my alternative dependent variables. Results are below. The only problem is, that now I do not know how to interpret the results...

[![enter image description here][1]][1]

**ORIGINAL POST**

I have a multinomial logit model with 13 IVs and a dependent with three levels `cash`, `stock`, `mix`. `cash` is the base dependent variable.

The IVs are - `COLLATERAL` - a proportion of the acquirer's fixed assets to its total assets, `CASH` is a ratio of its cash balance to the deal's value, `LEVERAGE` is acquirer's leverage ratio (debt to equity), `CONTROL` is the acquirer's biggest shareholder stake, `CONTROLLOSS` is a product between `CONTROL` and deal's value to the acquirer's market cap, `RELSIZE` is a ratio of deal's value and acquirer's market cap, `QRATIO` is acquirer's q-ratio, `RUNUP` is acquirer's stock return over year preceding transaction, `REVENUEGROWTH` is the acquirer's compunded revenue growth three years before a transaction. Dummies are `INDUSTRY` (1 if acquirer and target are from the same industry), `DOMESTIC` (1 if both from the same country), `PRIVATETARGET` if the target is privately held and `COMMON_LAW` if the acquirer is domiciled in UK or Ireland. All my IVs are **individual-specific**, no alternative-specific IVs here.

Data are available [here][2].

As far as I know, we interpret results of a multinomial logit always as a comparison to the base dependent variable - so if I have as a base dependent `cash`, I interpret the coefficients in comparison to this base. This means that the result of a multinomial logit gives me two sets of coefficients - one for `stock` and one for `mix` - as shown below on the output of multinom function of `nnet` package in R.

[![multinom output][3]][3]


Here, we get two sets of coefficients - one for `stock`, one for `mix` - and we interpret the coefficients as changes in the probability of `stock` or `mix` occuring vs. `cash` occuring (loosely put).

Nevertheless, the output of bayesian model averaging of multinomial logit, which is done with the `mlogitBMA` package in R, is following:

[![BMA of multinomial logit][4]][4]

In this output, there is only one set of coefficients - the column EV. So how do we interpret this output? Am I missing something? Thank you! I can provide you with my code and data if necessary.


  [1]: https://i.sstatic.net/rbNNo.png
  [2]: http://s000.tinyupload.com/index.php?file_id=44769640509004552500
  [3]: https://i.sstatic.net/B9f4m.png
  [4]: https://i.sstatic.net/8gCxt.png