rddensity "too many variables specified r(103)" error - How to solve?

[Arnau Domenech]

I have a dataset that has all the companies of the SP 500 with their respective ESG scores (nESG_Scores) and and monthly stock returns (MLR). I want to do a Regression Discontinuity test with set thresholds, for which I only need to specify two variables, MLR and nESG_Scores (as the running variable). I have been able to do it with the "rdrobust" command but when I use the "rddensity" command (to use an additional model) I get the "too many variables specified r(103)" error, even though I am only specifing two variables. Anyone why this happens and how to solve it?

My commands are:

. rdrobust MLR nESG_Score, c(62) kernel(triangular)
Mass points detected in the running variable.

Sharp RD estimates using local polynomial regression.

Cutoff c = 62 | Left of c Right of c Number of obs = 493
-------------------+---------------------- BW type = mserd
Number of obs | 396 97 Kernel = Triangular
Eff. Number of obs | 37 50 VCE method = NN
Order est. (p) | 1 1
Order bias (q) | 2 2
BW est. (h) | 8.406 8.406
BW bias (b) | 13.729 13.729
rho (h/b) | 0.612 0.612
Unique obs | 54 24

Outcome: MLR. Running variable: nESG_Score.
--------------------------------------------------------------------------------
Method | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------------+------------------------------------------------------------
Conventional | .00584 .03753 0.1556 0.876 -.067716 .079396
Robust | - - 0.1642 0.870 -.085712 .101384
--------------------------------------------------------------------------------
Estimates adjusted for mass points in the running variable.

.

. rddensity MLR nESG_Score, c(62) kernel(triangular)
too many variables specified
r(103);

.

[Nick Cox]

rddensity from the Stata Journal expects a single variable.