marginal effect when dependent variable is IHS transformed

[econ]

I have a following model:

y_i=alpha+beta X_i+gamma D_i+epsilon_i

where y_i is transformed using inverse hyperbolic sine (asinh) because of negative and positive values in the raw data, X is continuous variable and D is dummy variable. Suppose the estimated gamma coefficient is 0.20. How do you interpret this? I do know how to interpret when the explanatory variable is continuous, like X_i here.

[Dimitriy V. Masterov]

Take a look here:

Except for very small values of y, the inverse sine is approximately equal to log(2y_i) or log(2)+log(y_i), and so it can be interpreted in exactly the same way as a standard logarithmic dependent variable. For example, if the coefficient on "urban" is 0.1, that tells us that urbanites have approximately 10 percent higher wealth than non-urban people.

[econ]

Take a look here:

Thank you very much.