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Stochastic Growth In The United States And Euro Area

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  • Peter N. Ireland

Abstract

This paper estimates, using data from the United States and Euro Area, a two-country stochastic growth model in which both neutral and investment-specific technology shocks are nonstationary but cointegrated across economies. The results point to large and persistent swings in productivity, both favorable and adverse, originating in the US but not transmitted to the EA. More specifically, the results suggest that while the EA missed out on the period of rapid investment-specific technological change enjoyed in the US during the 1990s, it also escaped the stagnation in neutral technological progress that plagued the US in the 1970s.
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Suggested Citation

  • Peter N. Ireland, 2013. "Stochastic Growth In The United States And Euro Area," Journal of the European Economic Association, European Economic Association, vol. 11(1), pages 1-24, February.
  • Handle: RePEc:bla:jeurec:v:11:y:2013:i:1:p:1-24
    DOI: j.1542-4774.2012.01108.x
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    File URL: http://hdl.handle.net/10.1111/j.1542-4774.2012.01108.x
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    References listed on IDEAS

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    1. Backus, David K. & Smith, Gregor W., 1993. "Consumption and real exchange rates in dynamic economies with non-traded goods," Journal of International Economics, Elsevier, vol. 35(3-4), pages 297-316, November.
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    4. Federico Mandelman & Pau Rabanal & Juan Francisco Rubio-Ramirez & Diego Vilan, 2011. "Investment Specific Technology Shocks and International Business Cycles: An Empirical Assessment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 136-155, January.
    5. Coeurdacier, Nicolas & Kollmann, Robert & Martin, Philippe, 2010. "International portfolios, capital accumulation and foreign assets dynamics," Journal of International Economics, Elsevier, vol. 80(1), pages 100-112, January.
    6. Plutarchos Sakellaris & Focco Vijselaar, 2005. "Capital quality improvement and the sources of economic growth in the euro area," Economic Policy, CEPR;CES;MSH, vol. 20(42), pages 267-306, April.
    7. Peter Ireland & Scott Schuh, 2008. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 473-492, July.
    8. Alejandro Justiniano & Giorgio Primiceri & Andrea Tambalotti, 2011. "Investment Shocks and the Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 101-121, January.
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    Citations

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    Cited by:

    1. Federico Mandelman & Pau Rabanal & Juan Francisco Rubio-Ramirez & Diego Vilan, 2011. "Investment Specific Technology Shocks and International Business Cycles: An Empirical Assessment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 136-155, January.
    2. Naohisa Hirakata & Takushi Kurozumi, 2013. "The International Finance Multiplier in Business Cycle Fluctuations," IMES Discussion Paper Series 13-E-12, Institute for Monetary and Economic Studies, Bank of Japan.
    3. repec:eee:inecon:v:111:y:2018:i:c:p:143-158 is not listed on IDEAS
    4. KANO, Takashi, 2016. "Exchange Rates and Fundamentals: A General Equilibrium Exploration," Discussion paper series HIAS-E-19, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    5. Akkoyun, Hüseyin Çağrı & Arslan, Yavuz & Kılınç, Mustafa, 2017. "Risk sharing and real exchange rates: The role of non-tradable sector and trend shocks," Journal of International Money and Finance, Elsevier, vol. 73(PA), pages 232-248.
    6. Takashi Kano, 2013. "Exchange Rates and Fundamentals: Closing a Two-country Model," CAMA Working Papers 2013-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Kapetanios, George & Price, Simon & Theodoridis, Konstantinos, 2015. "A new approach to multi-step forecasting using dynamic stochastic general equilibrium models," Economics Letters, Elsevier, vol. 136(C), pages 237-242.
    8. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    9. repec:cup:macdyn:v:21:y:2017:i:03:p:555-598_00 is not listed on IDEAS
    10. Francesca Marino, 2016. "The Italian productivity slowdown in a Real Business Cycle perspective," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 63(2), pages 171-193, June.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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