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Modelling a complex world: Improving macro-models

Author

Listed:
  • Warwick J. McKibbin
  • Andrew Stoeckel

Abstract

Macro models have come under criticism for their ability to understand or predict major economic events such as the global financial crisis and its aftermath. Some of that criticism is warranted; but, in our view, much is not. This paper contributes to the debate over the adequacy of benchmark DSGE models by showing how three extensions, which are features that have characterized the global economy since the early 2000s, are necessary to improve our understanding of global shocks and policy insights. The three extensions are to acknowledge and model the entire global economy and the linkage through trade and capital flows; to allow for a wider range of relative price variability by moving to multiple sector models rather than a single good model; and to allow for changes in risk perceptions which propagate through financial markets and adjustments in the real economy. These extensions add some complexity to large scale macromodels, but without them policy models can oversimplify things, allowing misinterpretations of shocks and therefore costly policy mistakes to occur. Using oversimplified models to explain a complex world makes it more likely there will be “puzzles”. The usefulness of these extensions is demonstrated in two ways; first, by briefly revisiting some historical shocks to show how outcomes can be interpreted that make sense within a more complex DSGE framework; then, by making a contemporary assessment of the implications from the proposed large fiscal stimulus and the bans on immigration by the Trump administration which have both sectoral and macroeconomic implications that interact.

Suggested Citation

  • Warwick J. McKibbin & Andrew Stoeckel, 2017. "Modelling a complex world: Improving macro-models," CAMA Working Papers 2017-56, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2017-56
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    References listed on IDEAS

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    1. McKibbin, Warwick J & Vines, David, 2000. "Modelling Reality: The Need for Both Inter-temporal Optimization and Stickiness in Models for Policy-Making," Oxford Review of Economic Policy, Oxford University Press, vol. 16(4), pages 106-137, Winter.
    2. Tony Hall & Jan Jacobs & Adrian Pagan, "undated". "Macro-Econometric System Modelling @75," NCER Working Paper Series 95, National Centre for Econometric Research.
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    4. Adam Cagliarini & Warwick McKibbin, 2010. "Global Relative Price Shocks: The Role of Macroeconomic Policies," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    5. Warwick J. McKibbin & Andrew Stoeckel, 2009. "Modelling the global financial crisis," Oxford Review of Economic Policy, Oxford University Press, vol. 25(4), pages 581-607, Winter.
    6. Blanchard, Olivier J, 1985. "Debt, Deficits, and Finite Horizons," Journal of Political Economy, University of Chicago Press, vol. 93(2), pages 223-247, April.
    7. David F Hendry & John N J Muellbauer, 2018. "The future of macroeconomics: macro theory and models at the Bank of England," Oxford Review of Economic Policy, Oxford University Press, vol. 34(1-2), pages 287-328.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Modelling a complex world: Improving macro-models
      by Christian Zimmermann in NEP-DGE blog on 2017-09-22 21:04:25

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    Cited by:

    1. Georgiadis, Georgios & Hildebrand, Sebastian & Ricci, Martino & Schumann, Ben & van Roye, Björn, 2021. "ECB-Global 2.0: a global macroeconomic model with dominant-currency pricing, tariffs and trade diversion," Working Paper Series 2530, European Central Bank.
    2. Dieppe, Alistair & Georgiadis, Georgios & Ricci, Martino & Van Robays, Ine & van Roye, Björn, 2018. "ECB-Global: Introducing the ECB's global macroeconomic model for spillover analysis," Economic Modelling, Elsevier, vol. 72(C), pages 78-98.
    3. Lee, Jong-Wha & McKibbin, Warwick J., 2018. "Service sector productivity and economic growth in Asia," Economic Modelling, Elsevier, vol. 74(C), pages 247-263.
    4. Giovannini, Massimo & Hohberger, Stefan & Kollmann, Robert & Ratto, Marco & Roeger, Werner & Vogel, Lukas, 2019. "Euro Area and US external adjustment: The role of commodity prices and Emerging Market shocks," Journal of International Money and Finance, Elsevier, vol. 94(C), pages 183-205.

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    More about this item

    Keywords

    Macroeconomics; Models; Risk; Relative Prices; Sectors; DSGE;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy
    • F4 - International Economics - - Macroeconomic Aspects of International Trade and Finance

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