Let be the probability generating function. For the series can be differentiated term by term: is finite, even without a finite claim-count expected value. Multiply the Panjer claim-count class recurrence by and put . Then
Hence
This argument is valid throughout the open unit disk. Values at boundary points may be obtained by a limit when the required derivatives exist; one need not assume to establish the identity.
For a Poisson distribution of parameter , its probability generating function is . Applying the law of total expectation to the Poisson mixture gives
Thus
For the absolute value of the integrand is bounded by one, so this identity always exists as a Laplace transform of the positive mixing variable. An extension to requires the corresponding moment-generating function to be finite; the conditional computation itself does not guarantee positive exponential moments.
The exponential distribution with rate has moment-generating function for . Shifting it by multiplies the moment-generating function by . Therefore the shifted-exponential Poisson mixture has probability generating function
The probability generating function converges and is analytic for , and in particular is finite for real .
Write and , so . The factor is the probability generating function of , while is that of a geometric distribution on , with . Choose and independently. The product rule for the probability generating function of a sum of independent counts then proves . The support-zero convention for is essential here.
The convolution of independent random variables gives the finite sum
Taking the logarithmic derivative of the probability generating function gives
Compare coefficients of , for . The left side is , and the right side is . Hence the shifted-exponential Poisson count recursion is
The constant and linear coefficients supply the starting values
These two values determine every subsequent probability by the recursion. The negative second term does not mean that the distribution has negative probabilities: the convolution formula exhibits every as a sum of nonnegative quantities.
At the independent Poisson distribution component is identically zero and the count has a geometric distribution. Both the finite sum and the recursion reduce to . Consequently the Panjer claim-count class parameters are
Although the shifted model initially has positive , this zero-shift boundary case is well defined.

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