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Assessing Markov chain approximations: A minimal econometric approach

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  • Silos, Pedro

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  • Silos, Pedro, 2006. "Assessing Markov chain approximations: A minimal econometric approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 1063-1079, June.
    • Handle: RePEc:eee:dyncon:v:30:y:2006:i:6:p:1063-1079
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    2. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
    3. Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-396, March.
    4. Christopher Otrok & B. Ravikumar & Charles H. Whiteman, 2002. "Evaluating asset-pricing models using the Hansen-Jagannathan bound: a Monte Carlo investigation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 149-174.
    5. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
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    7. S. Rao Aiyagari, 1994. "Uninsured Idiosyncratic Risk and Aggregate Saving," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 659-684.
    8. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    9. Campbell, John Y., 1994. "Inspecting the mechanism: An analytical approach to the stochastic growth model," Journal of Monetary Economics, Elsevier, vol. 33(3), pages 463-506, June.
    10. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    11. Gregory, Allan W & Smith, Gregor W, 1991. "Calibration as Testing: Inference in Simulated Macroeconomic Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 297-303, July.
    12. John Geweke, 1999. "Computational Experiments and Reality," Computing in Economics and Finance 1999 401, Society for Computational Economics.
    13. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
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    15. Fernandez-Villaverde, Jesus & Francisco Rubio-Ramirez, Juan, 2004. "Comparing dynamic equilibrium models to data: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 123(1), pages 153-187, November.
    16. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979.
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    Cited by:

    1. Silos, Pedro, 2007. "Housing, portfolio choice and the macroeconomy," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2774-2801, August.
    2. Lu, Changxiang & Ye, Yong & Fang, Yongjun & Fang, Jiaqi, 2023. "An optimal control theory approach for freight structure path evolution post-COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    3. Wei Kang & Sergio J. Rey, 2018. "Conditional and joint tests for spatial effects in discrete Markov chain models of regional income distribution dynamics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(1), pages 73-93, July.

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