How to interpret this relationship between coefficients in linear regression?

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we are having the following problem:

Suppose a linear regression model with the following form

$$ Y = B_0 + B_1 X_1 + B_2 X_2 + e$$

if we run the regression (with OLS) we end up with the following results

$$X_i$$ Estimation $$(B_i)$$ Standard deviation
1 0.85*** (0.12)
2 0.82*** (0.26)

where *** means p-value<0,001

The question that we are having with our team is the next:

Can we say this? $$B_1 > B_2$$

Since $$.85 > .82$$

or do we have to take into consideration the standard deviation? reason for which we couldn't assume the previous result.

The possible answer that we are thinking of are:

  1. With the evidence we can't say that B1>B2 since if we have into account the standard deviation the CI overlaps

  2. We can say that, on average, B1>B2, but is not statistically significant

  3. On average, B1>B2

  4. Other option/procedures...

Thank you in advance, if it is possible, it would help any paper that justifies the answer