How to prove $I-BA$ is invertible Show that $I-BA$ is invertible if $I-AB$ is invertible. And also, we have to prove that eigenvalues are same for $AB$ and $BA$
Till now, I used the equation $(I-AB)(I-AB)^{-1}=I$ which gives $(I-AB)AB(I-AB)^{-1}=AB$ but I don't know how to proceed further.
Any hint would be sufficient !
 A: Suppose $I - AB$ is invertible.
Suppose $(I - BA)x = 0$.
Then :
$$BAx = x$$
so
$$ABAx = Ax$$
or, what is the same,
$$(I - AB)Ax = 0$$
Since $I - AB$ is invertible, this last equality implies
$$Ax = 0$$
Hence $x = BAx = 0$. Thus the only solution of $(I - BA)x = 0$ is $x = 0$, so $I - BA$ is invertible.
A: Let's show that $AB$ and $BA$ have the same eigenvalues.
First, let $\lambda$ be a nonzero eigenvalue of $AB$; then $ABv=\lambda v$, for some $v\ne0$. Therefore $BA(Bv)=B(\lambda v)=\lambda(Bv)$ and so $\lambda$ is an eigenvalue of $BA$ (because $Bv\ne0$).
If $0$ is an eigenvalue of $AB$, at least one of $A$ and $B$ is not invertible. Thus also $BA$ is not invertible and has the eigenvalue $0$.

Now, the eigenvalues of $C$ are the (complex) numbers that make $C-\lambda I$ not invertible. Saying that $AB-I$ is invertible is the same as saying that $1$ is not an eigenvalue of $AB$; thus it is not an eigenvalue of $BA$ either.
A: Question 1: Let $A$ and $B$ be square matrices of the same order. Prove that $I-AB$ is invertible if and only if $I-BA$ is invertible.
Proof: Let $C$ be the inverse of $I-AB$. Then
$$I-BA=I-BIA=I-BC(I-AB)A=I-BCA(I-BA),$$
which gives us
$$(I-BA)(I+BCA)=I.$$
Thus $I-BA$ is invertible with the inverse $I+BCA$.
Question 2: Let $A$ be an $m\times n$ and $B$ be an $n\times m$ matrix with $m\le n$. Prove that $AB$ and $BA$ have the same nonzero eigenvalues, counting multiplicities, with $BA$ having an additional $n-m$ eigenvalues equal to $0$.
Proof: (It's a proof by C. R. Johnson and E. Schreiner published in American Mathematical Monthly 103 (1996), 578-582)
First notice that the $(m+n)\times (m+n)$ partitioned matrices
$$\left[ 
\begin{array}{cc}
AB & 0\\
B & 0
\end{array}
\right]
\qquad \text{and} \qquad
\left[ 
\begin{array}{cc}
0 & 0\\
B & BA
\end{array}
\right]$$
are similar to each other via the partitioned block calculation:
$$\left[ 
\begin{array}{cc}
AB & 0\\
B & 0
\end{array}
\right]
\left[ 
\begin{array}{cc}
I_m & A\\
0 & I_n
\end{array}
\right]=
\left[ 
\begin{array}{cc}
AB & ABA\\
B & BA
\end{array}
\right]=
\left[ 
\begin{array}{cc}
I_m & A\\
0 & I_n
\end{array}
\right]
\left[ 
\begin{array}{cc}
0 & 0\\
B & BA
\end{array}
\right].
$$
Since
$$\left[ 
\begin{array}{cc}
I_m & A\\
0 & I_n
\end{array}
\right]
$$
is invertible, it provides the similarity. Beacause
$$\left[ 
\begin{array}{cc}
AB & 0\\
B & 0
\end{array}
\right]
$$
is block triangular, its eigenvalues are those of the two diagonal blocks, $AB$ and the $n\times n$ zero matrix (See eigenvalues of a block matrix or the-eigenvalues-of-a-block-matrix). Similarly, the eigenvalues of
$$
\left[ 
\begin{array}{cc}
0 & 0\\
B & BA
\end{array}
\right]
$$
are the eigenvalues of $BA$, together with $m$ zeroes. Because the two partitioned matrices are similar and similar matrices have the same eigenvalues (see similar matrices have the same eigenvalues), $AB$ and $BA$ must have the same nonzero eigenvalues (counting multiplicities) and the additional $n-m$ eigenvalues of $BA$ must all be $0$.

Alternate Proof: (It's a proof from the book Matrix Analysis (Roger A. Horn, Charles R. Johnson) suggested in Exercise 9, page 55.)
(a) First, suppose that $A,B\in M_n$ and that at least one of them is invertible, Show that $AB$ is similar to $BA$ and hence the characteristic polynomials of $AB$ and $BA$ are the same. Hint: If $A$ is invertible, $BA=A^{-1}(AB)A$.
(b) Show that if $A,B\in M_n$ are both singular, $AB$ and $BA$ have the same eigenvalues, counting  multiplicities. $Hint:$ Consider the following analytic argument. For all sufficiently  small $\varepsilon>0$, $A_{\varepsilon}:=A+\varepsilon I$ is invertible; thus $A_{\varepsilon}B$ and $BA_{\varepsilon}$ are similar and hence the characteristic polynomials of $A_{\varepsilon}B$ and $BA_{\varepsilon}$ are the same. If we now let $\varepsilon \to 0$, similarity may fail in the limit, but equality of the characteristic polynomials continues to hold since $p_{A_{\varepsilon}B}(t)=\det{(tI-A_{\varepsilon}B)}$ depends continuously on $\varepsilon$. Thus, $AB$ and $BA$ have the same characteristic polynomials and therefore the same eigenvalues, counting multiplicities.
(Far now parts (a) and (b) are the same as the answer of @A.G.)
(c) Finally, if $A\in M_{m, n}$ and $B\in M_{n, m}$, with $m<n$,show that $AB$ and $BA$ have the same eigenvalues, counting multiplicities, except that $BA$ has an additional $n-m$ eigenvalues equal to $0$; equivalently, $p_{BA}(t)=t^{n-m}p_{AB}(t)$. Hint: Make $n$ by $n$ matrices out of both $A$ (by appending $0$ rows) and $B$ (by appending $0$ columns), apply the last result, and compare the two new products (appropriately partitioned) to the old ones.
A: Hint: prove that
$$
\det(\lambda I-AB)=\det(\lambda I-BA).
$$
P.S. Matrices has to be square otherwise the statement about eigenvalues is not correct.
Edit:
There is a nice proof of this fact:


*

*If $A$ is invertible then
$$
AB=ABAA^{-1}=A(BA)A^{-1},
$$
and, hence, $AB$ and $BA$ are similar. Similar matrices have the same characteristic polynomial.

*If $A$ is singular then it can be disturbed to a nonsingular $A_\epsilon$ such that $A_\epsilon\to A$ when $\epsilon\to 0$ (for example,$A_\epsilon=A+\epsilon I$). By the first item
$$
\det(\lambda I-A_\epsilon B)=\det(\lambda I-BA_\epsilon).
$$
Now take the limit when $\epsilon\to 0$ and use the continuous dependence of determinants on matrix components.

