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RBCs and DSGEs:The Computational Approach to Business Cycle Theory and Evidence

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Real Business Cycle (RBC) and Dynamic Stochastic General Equilibrium (DSGE) methods have become essential components of the macroeconomist’s toolkit. This literature review stresses recently developed (often Bayesian) techniques for computation and inference, providing a supplement to the Romer (2006) textbook treatment which stresses theoretical issues. Many computational aspects are illustrated with reference to the simple divisible labour RBC model familiar to graduate students from King, Plosser and Rebelo (1988), Christiano and Eichenbaum (1992), Campbell (1994) and Romer (2006). Code and US data to replicate the computations are provided on the Internet, together with a number of appendices providing background details.

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Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number DP2007/15.

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Length: 62 p.
Date of creation: Nov 2007
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Handle: RePEc:nzb:nzbdps:2007/15

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Cited by:
  1. Creel, Michael & Kristensen, Dennis, 2011. "Indirect Likelihood Inference," Dynare Working Papers, CEPREMAP 8, CEPREMAP.
  2. Ida Wolden Bache & Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2009. "Combining VAR and DSGE forecast densities," Working Paper, Norges Bank 2009/23, Norges Bank.
  3. Ramiro Rodríguez Revilla, 2011. "Modelos de equilibrio general dinámicos y estocásticos para Colombia 1995-2011," REVISTA ECOS DE ECONOMÍA, UNIVERSIDAD EAFIT, UNIVERSIDAD EAFIT.
  4. da Silva, Marcos Soares & Divino, Jose Angelo, 2013. "The role of banking regulation in an economy under credit risk and liquidity shock," The North American Journal of Economics and Finance, Elsevier, Elsevier, vol. 26(C), pages 266-281.
  5. Guha, Puja, 2013. "Macroeconomic effects of international remittances: The case of developing economies," Economic Modelling, Elsevier, Elsevier, vol. 33(C), pages 292-305.

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