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Alternative methods of solving state-dependent pricing models

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  • Edward S. Knotek
  • Stephen J. Terry

Abstract

We use simulation-based techniques to compare and contrast two methods for solving state-dependent pricing models: discretization, which solves and simulates the model on a grid; and collocation, which relies on Chebyshev polynomials. While both methods produce qualitatively similar results, statistically significant quantitative differences do arise. We present evidence favoring discretization over collocation in this context, given a lack of robustness in the latter.

Suggested Citation

  • Edward S. Knotek & Stephen J. Terry, 2008. "Alternative methods of solving state-dependent pricing models," Research Working Paper RWP 08-10, Federal Reserve Bank of Kansas City.
    • Handle: RePEc:fip:fedkrw:rwp08-10
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    3. Matthew Klepacz, 2018. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," 2018 Meeting Papers 145, Society for Economic Dynamics.
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    5. Matthew Klepacz, 2021. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," International Finance Discussion Papers 1316, Board of Governors of the Federal Reserve System (U.S.).
    6. David Berger, 2012. "Countercyclical Restructuring and Jobless Recoveries," 2012 Meeting Papers 1179, Society for Economic Dynamics.
    7. Joseph Vavra, 2014. "Inflation Dynamics and Time-Varying Volatility: New Evidence and an Ss Interpretation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 215-258.

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