Joint Distribution of two dependent Bernoulli Random Variables for $\rho=1$ Say we have two random variables $X\sim B(p_1),\ Y\sim B(p_2)$ where $B(p)=$  Bernoulli with probability $0\le p\le 1$. I am interested in the case when the correlation $\rho$ of $X,Y$ tends to $1$.
If we set events $A=\{X=1\}$, $B=\{Y=1\}$, the conditional probability property gives us
  $$\begin{align}\tag{1}
  P(A\cap B) = P(A\mid B)\cdot P(B)\\ = P(B\mid A)\cdot P(A)
  \end{align}$$
When $\rho=1$ we must have $P(A\mid B)=P(B\mid A)=1$ (since one event implies the other). Equation $(1)$ then yields
  $$P(A) = P(B)$$
Furthermore, if correlation is high (= tending to 1), then whenever event $A$ occurs then $B$ must also occur (and vice versa). So the probabilities of $A,B$ should be 
  $$P(A)=P(B)=\max(p_1,p_2)\tag{2}$$
However, for any $\rho=1-\epsilon$ with $\epsilon>0$, we still have $P(A)=p_1$ and $P(B)=p_2$ as per definition.
So can $(2)$ even be correct? What am I missing?

Unfortunately, Joint distribution of dependent Bernoulli Random variables only discusses non-deterministic sequences, so it doesn't quite apply.
 A: The apparent inconsistency is due to the fact that $\rho$ cannot take on all values between $-1$ and $1$ given specific values for $p_1$ and $p_2$.
Using the definition of a correlation coefficient
$$\rho={{Cov(x_1,x_2)} \over {\sqrt{Var(x_1)Var(x_2)}}}={{\text{Pr}(x_1=1,x_2=1)-p_1 p_2}\over{\sqrt{p_1(1-p_1)p_2(1-p_2)}}}$$
and noting that $\text{Pr}(x_1=1,x_2=1)\leq \text{Min}(p_1,p_2)$ we can find the maximum value of $\rho$ for all possible values of $p_1$ and $p_2$ (here using Mathematica):
sol = Maximize[{(P11 - p1 p2)/Sqrt[p1 (1 - p1) p2 (1 - p2)], 
    0 < p1 < 1 && 0 < p2 < 1 && 0 < P11 <= Min[p1, p2]}, P11][[1]]

$$\begin{array}{cc}
 \{ & 
\begin{array}{cc}
 \sqrt{\frac{\text{p1} (\text{p2}-1)}{(\text{p1}-1) \text{p2}}} & \left(0<\text{p2}<\frac{1}{2}\land 0<\text{p1}\leq \text{p2}\right)\lor \left(\frac{1}{2}\leq \text{p2}<1\land \text{p1}=\text{p2}\right)\lor \left(\frac{1}{2}\leq \text{p2}<1\land 0<\text{p1}<\text{p2}\right) \\
 \sqrt{\frac{(\text{p1}-1) \text{p2}}{\text{p1} (\text{p2}-1)}} & \left(0<\text{p2}<\frac{1}{2}\land \text{p2}<\text{p1}<1\right)\lor \left(\frac{1}{2}\leq \text{p2}<1\land \text{p2}<\text{p1}<1\right) \\
 -\infty  & \text{True} \\
\end{array}
 \\
\end{array}$$
ContourPlot[sol, {p1, 0, 1}, {p2, 0, 1}, ContourLabels -> True]


In short, $\rho=1$ can only occur when $p_1=p_2$.
