Dynamic Programming with Hermite Approximation / Yongyang Cai, Kenneth L. Judd.

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Cai, Yongyang

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w18540.Publication details: Cambridge, Mass. National Bureau of Economic Research 2012.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: Numerical dynamic programming algorithms typically use Lagrange data to approximate value functions over continuous states. Hermite data is easily obtained from solving the Bellman equation and can be used to approximate value functions. We illustrate this method with one-, three-, and six-dimensional examples. We find that value function iteration with Hermite approximation improves accuracy by one to three digits using little extra computing time. Moreover, Hermite approximation is significantly faster than Lagrange for the same accuracy, and this advantage increases with dimension.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w18540 (Browse shelf(Opens below))	Not For Loan

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November 2012.

Numerical dynamic programming algorithms typically use Lagrange data to approximate value functions over continuous states. Hermite data is easily obtained from solving the Bellman equation and can be used to approximate value functions. We illustrate this method with one-, three-, and six-dimensional examples. We find that value function iteration with Hermite approximation improves accuracy by one to three digits using little extra computing time. Moreover, Hermite approximation is significantly faster than Lagrange for the same accuracy, and this advantage increases with dimension.