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Howard's policy iteration algorithm Consider the Brock-Mirman problem: to maximize E0 ∑t=0^∞ β^t lnct, subject to ct kt 1 ≤A kt^α, k0 given, A>0,1>α>0, where {} is an i.i.d. sequence with lndistributed according to a normal distribution with mean zero and variance σ^2. Consider the following algorithm. Guess at a policy of the form kt 1= h0(A kt^α) for any constant h0 ∈(0,1). Then form J0(k0, θ0)=E0 ∑t=0^∞ β^t ln(A kt^α-h0 A kt^α) . Next choose a new policy h1 by maximizing ln(A k^αθ-k^') βE J0(
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