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Investment Shocks, Sticky Prices, and the Endogenous Relative Price of Investment

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  • Alban Moura

    (Central Bank of Luxembourg)

Abstract

This paper estimates a two-sector DSGE model of the U.S. economy with two key ingredients: (i) an explicit distinction between shocks to investment demand and shocks to investment supply; (ii) sector-specific pricing frictions. According to the estimation results, investment demand shocks are more important than investment supply shocks in driving aggregate fluctuations. Furthermore, sticky investment prices are important to capture the effects of sector-specific technology shocks, in particular recessionary investment supply shocks. Finally, the model suggests that the relative price of investment provides a poor indicator of relative technology in short to medium horizons. (Copyright: Elsevier)

Suggested Citation

  • Alban Moura, 2018. "Investment Shocks, Sticky Prices, and the Endogenous Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 27, pages 48-63, January.
    • Handle: RePEc:red:issued:16-315
    DOI: 10.1016/j.red.2017.11.004
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    Cited by:

    1. Fève, Patrick & Sanchez, Pablo Garcia & Moura, Alban & Pierrard, Olivier, 2021. "Costly default and skewed business cycles," European Economic Review, Elsevier, vol. 132(C).
    2. Yury N. Vorobyov & Elena I. Vorobyova, 2019. "Investment potential of Russia’s economy: Opportunities for financing the development," Journal of New Economy, Ural State University of Economics, vol. 20(1), pages 41-60, March.
    3. Alban Moura, 2023. "Trend breaks and the long-run implications of investment-specific technological progress," Applied Economics Letters, Taylor & Francis Journals, vol. 30(16), pages 2270-2275, September.
    4. Aydan Dogan, 2019. "Investment Specific Technology Shocks and Emerging Market Business Cycle Dynamics," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 34, pages 202-220, October.
    5. Alban Moura, 2020. "Total factor productivity and the measurement of neutral technology," BCL working papers 143, Central Bank of Luxembourg.
    6. Fève, Patrick & Moura, Alban & Pierrard, Olivier, 2022. "The fall in shadow banking and the slow U.S. recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    7. Nikolaos Charalampidis, 2020. "The U.S. Labor Income Share And Automation Shocks," Economic Inquiry, Western Economic Association International, vol. 58(1), pages 294-318, January.
    8. Emanuele Colombo Azimonti & Luca Portoghese & Patrizio Tirelli, 2022. "Covid-19 supply-side fiscal policies to escape the health-vs-economy dilemma," DEM Working Papers Series 208, University of Pavia, Department of Economics and Management.
    9. Nadav Ben Zeev, 2019. "Is There A Single Shock That Drives The Majority Of Business Cycle Fluctuations?," Working Papers 1906, Ben-Gurion University of the Negev, Department of Economics.
    10. Fève, Patrick & Sanchez, Pablo Garcia & Moura, Alban & Pierrard, Olivier, 2021. "Costly default and skewed business cycles," European Economic Review, Elsevier, vol. 132(C).
    11. Alban Moura, 2020. "LED: An estimated DSGE model of the Luxembourg economy for policy analysis," BCL working papers 147, Central Bank of Luxembourg.
    12. Cho, Daeha & Kim, Kwang Hwan, 2022. "Inefficient relative price fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    13. Moura, Alban, 2021. "Are neutral and investment-specific technology shocks correlated?," European Economic Review, Elsevier, vol. 139(C).
    14. Takuji Fueki & Shinnosuke Katsuki & Ichiro Muto & Yu Sugisaki, 2023. "Automation and Nominal Rigidities," IMES Discussion Paper Series 23-E-01, Institute for Monetary and Economic Studies, Bank of Japan.
    15. Alban Moura & Olivier Pierrard, 2022. "How well do DSGE models with real estate and collateral constraints fit the data?," BCL working papers 168, Central Bank of Luxembourg.
    16. Ivashchenko, Sergey & Mutschler, Willi, 2020. "The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models," Economic Modelling, Elsevier, vol. 88(C), pages 280-292.
    17. Aydan Dogan, 2019. "Investment Specific Technology Shocks and Emerging Market Business Cycle Dynamics," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 34, pages 202-220, October.
    18. Fabio Massimo Piersanti & Patrizio Tirelli, 2020. "Endogenous Productivity Dynamics in a Two-Sector Business Cycle Model," Working Papers 434, University of Milano-Bicocca, Department of Economics, revised Feb 2020.
    19. Daeha Cho & Kwang Hwan Kim, 2020. "Inefficient Relative Price Fluctuations," Working papers 2020rwp-171, Yonsei University, Yonsei Economics Research Institute.
    20. Ma, Xiaohan & Samaniego, Roberto, 2022. "Business cycle dynamics when neutral and investment-specific technology shocks are imperfectly observable," Journal of Mathematical Economics, Elsevier, vol. 101(C).
    21. Seunghoon Na & Hyunseung Oh, 2020. "Computerizing Households and the Role of Investment-Specific Productivity in Business Cycles," International Finance Discussion Papers 1292, Board of Governors of the Federal Reserve System (U.S.).

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    More about this item

    Keywords

    Investment shocks; Sticky prices; Relative price of investment; Multisector DSGE model;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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