Hello everyone,

I am using probit model in Stata 16.1 to identify [dependent var] whether a firm chooses to donate money to a particular race [A firm can choose to donate or not donate, and to whom to donate, at its will]. The explanatory variable is the ratio of (proportion) directors on the firm’s board, who belong to that race.

Code:
As you may notice through summary stats, only around 9.94% of the firms choose to donate toward the development of the race, and that the proportion of directors from this racial background on firms’ boards is very low (11.67%).
sum activity_for_race ratio_board_race

Variable         Obs        Mean    Std. Dev.       Min    Max
activity_f~e       3,772    .0994168    .2992604          0    1
ratio_boar~e       3,772    .1167132    .0931283          0    .546

When I use xtprobit command, as predicted, I find that the higher the ratio of board of directors who belong to a particular race, the lower the probability that a firm will donate toward the development of that race.
xi: xtprobit activity_for_race ratio_board_race lag_roa size lag_firm_risk lag_firm_age lag_liquidity advertising_sales rd_sales higher_edu_ratio coefvar_age female_bod_ratio indep_bod_ratio  , vce(robust)
(1) (2)
VARIABLES activity_for_race /
ratio_board_race -1.950**
(0.835)
lag_roa 0.0262**
(0.0102)
size 0.222***
(0.0522)
lag_firm_risk -0.330***
(0.101)
lag_firm_age 0.339**
(0.133)
lag_liquidity -0.0702
(0.0595)
advertising_sales 0.0568*
(0.0336)
rd_sales 6.456*
(3.532)
higher_edu_ratio 0.305
(0.357)
coefvar_age 1.019
(1.075)
female_bod_ratio 0.913
(1.008)
indep_bod_ratio -0.762
(0.644)
lnsig2u 0.863***
(0.180)
Constant -5.418***
(0.851)
Observations 3,437 3,437
Number of co_code 1,075 1,075 
 The Margins command shows the following results:
margins, dydx(ratio_board_race) at(ratio_board_race=(0(0.1)0.6))
marginsplot, recast(line) recastci(rarea) ciopt(lcolor(navy) fcolor(ebblue) color(%20)) plot1opts(lcolor(navy) fcolor(ebblue%> 35))
----------------------------------------------------------------------------------
                 |            Delta-method
                 |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
ratio_board_race |
             _at |
              1  |  -.2044895   .0995239    -2.05   0.040    -.3995527   -.0094263
              2  |  -.1815109   .0794067    -2.29   0.022    -.3371451   -.0258767
              3  |  -.1595206    .060602    -2.63   0.008    -.2782983   -.0407429
              4  |  -.1388028   .0436096    -3.18   0.001     -.224276   -.0533296
              5  |  -.1195754   .0288116    -4.15   0.000    -.1760451   -.0631056
              6  |  -.1019893   .0165515    -6.16   0.000    -.1344296   -.0695489
              7  |  -.0861304   .0076791   -11.22   0.000     -.101181   -.0710797
----------------------------------------------------------------------------------

   Array 

Q1. The marginsplot shows an increasing (positive) line. However, because I have covered the whole range of explanatory variable, how is the probability [Effects on Pr(activity_for_race=1] negative for all the values of ratio_board_race ? How can I interpret this?

Q2. Does the Margins show that an increase in ratio (proportion) of directors from the race actually improve donation toward their own race communities, given the trend is toward lesser negative / 0?
I will very much appreciate if someone can clarify my doubt.

Thanks,
Nishant