The American Economic Review, Volume 97American Economic Association., 2007 |
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Página 697
... Stochastic Dynamics for Learning Uncer- tainty . So far , we have considered the case with homoskedastic Gaussian innovations to the state vector , which implies that Pr – 1 evolves in a deterministic fashion ( equation ( 4 ) ) . Never ...
... Stochastic Dynamics for Learning Uncer- tainty . So far , we have considered the case with homoskedastic Gaussian innovations to the state vector , which implies that Pr – 1 evolves in a deterministic fashion ( equation ( 4 ) ) . Never ...
Página 892
... stochastic domi- nance . This is useful as it allows us to derive results about the efficiency of the resulting net- works . For instance , if the utility derived by a node is a concave function of its degree , then second - order ...
... stochastic domi- nance . This is useful as it allows us to derive results about the efficiency of the resulting net- works . For instance , if the utility derived by a node is a concave function of its degree , then second - order ...
Página 1115
... stochastic discount factor is made to become arbitrarily large simply by choosing for ( 32 ) a sufficiently small value of T , no matter what value of k < ∞ has been given . Note that as k → ∞ for any given I > 0 , the moment ...
... stochastic discount factor is made to become arbitrarily large simply by choosing for ( 32 ) a sufficiently small value of T , no matter what value of k < ∞ has been given . Note that as k → ∞ for any given I > 0 , the moment ...
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EDMUND S PHELPS | 541 |
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ALMA COHEN AND LIRAN EINAV | 745 |
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