Estimating baseline real business cycle models of the Australian economy
Abstract
This paper is concerned with the issues that arise in building a small Dynamic Stochastic General Equilibrium (DSGE) model of the Australian economy. Our ultimate objective is to build a model that can be used to study long run economic growth and the business cycle. We agree with Cooley and Prescot�s (1995) view that these are phenomena to be studied jointly rather than separately. Adopting this view has several implications for what constitutes the essential components of our a model. We see these as being: a major role for a persistent technology shock in driving economic activity; and consistency with a version of the Ramsey-Cass-Koopmans (RCK) exogenous growth model. Without the former it is not possible to generate realistic business cycle features; demand shocks alone are insuffcient see Harding and Pagan (2007). The RCK exogenous growth model remains the simplest model available to encompass the salient features of economic growth which is why we rate it as essential. We also take the methodological stance that it is desirable to obtain a satisfactory baseline model before adding other desirable features such as: money; openness to international trade, capital flows, and immigration; and price and wage stickiness. In short we see small real business cycle (RBC) models as the natural starting point for our work.Download Info
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 33556.Length:
Date of creation: 26 Feb 2008
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Handle: RePEc:pra:mprapa:33556
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Related research
Keywords: Real business cycle; stochastic growth model; technology shock; persistence;Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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