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Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks

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  • S. Sirakaya
  • Stephen Turnovsky
  • M. Alemdar

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  • S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 185-206, May.
    • Handle: RePEc:kap:compec:v:27:y:2006:i:2:p:185-206
    DOI: 10.1007/s10614-006-9024-8
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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Duffy, John & McNelis, Paul D., 2001. "Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1273-1303, September.
    3. Kim, Jinill & Kim, Sunghyun Henry, 2003. "Spurious welfare reversals in international business cycle models," Journal of International Economics, Elsevier, vol. 60(2), pages 471-500, August.
    4. Gagnon, Joseph E, 1990. "Solving the Stochastic Growth Model by Deterministic Extended Path," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 35-36, January.
    5. Tauchen, George, 1990. "Solving the Stochastic Growth Model by Using Quadrature Methods and Value-Function Iterations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 49-51, January.
    6. Christiano, Lawrence J. & Fisher, Jonas D. M., 2000. "Algorithms for solving dynamic models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 24(8), pages 1179-1232, July.
    7. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-1185, July.
    8. William A. Brock & Leonard J. Mirman, 2001. "Optimal Economic Growth And Uncertainty: The Discounted Case," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 1, pages 3-37, Edward Elgar Publishing.
    9. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    10. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    11. Ingram, Beth Fisher, 1990. "Solving the Stochastic Growth Model by Backsolving with an Expanded Shock Space," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 37-38, January.
    12. Burkhard Heer & Alfred Maußner, 2024. "Dynamic General Equilibrium Modeling," Springer Texts in Business and Economics, Springer, edition 3, number 978-3-031-51681-8, August.
    13. Donald A. Walker (ed.), 2000. "Equilibrium," Books, Edward Elgar Publishing, volume 0, number 1585.
    14. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979.
    15. Charles I. Jones, 1995. "Time Series Tests of Endogenous Growth Models," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 495-525.
    16. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    17. Jonathan Eaton, 1981. "Fiscal Policy, Inflation and the Accumulation of Risky Capital," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 48(3), pages 435-445.
    18. Christiano, Lawrence J, 1990. "Solving the Stochastic Growth Model by Linear-Quadratic Approximation and by Value-Function Iteration," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 23-26, January.
    19. McGrattan, Ellen R, 1990. "Solving the Stochastic Growth Model by Linear-Quadratic Approximation," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 41-44, January.
    20. Alemdar, Nedim M. & Ozyildirim, Suheyla, 1998. "A genetic game of trade, growth and externalities," Journal of Economic Dynamics and Control, Elsevier, vol. 22(6), pages 811-832, June.
    21. Ozyildirim, Suheyla & Alemdar, Nedim M., 2000. "Learning the optimum as a Nash equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 24(4), pages 483-499, April.
    22. Ellen R. McGrattan, 1998. "Application of weighted residual methods to dynamic economic models," Staff Report 232, Federal Reserve Bank of Minneapolis.
    23. Sims, Christopher A, 1990. "Solving the Stochastic Growth Model by Backsolving with a Particular Nonlinear Form for the Decision Rule," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 45-47, January.
    24. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
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    1. Burkhard Heer & Alfred Maußner, 2024. "Dynamic General Equilibrium Modeling," Springer Texts in Business and Economics, Springer, edition 3, number 978-3-031-51681-8, August.
    2. Lim, G.C. & McNelis, Paul D., 2008. "Computational Macroeconomics for the Open Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262123061, December.
    3. Adalbert Mayer, 2022. "An Agent-Based Macroeconomic Model with Endogenous Intertemporal Decision Rules," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(4), pages 548-579, October.
    4. G. C. Lim & Paul D. McNelis, 2006. "Fiscal and Current Account Balances in a Model with Sticky Prices and Distortionary Taxes," Melbourne Institute Working Paper Series wp2006n21, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

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