IDEAS home Printed from https://ideas.repec.org/a/eee/chieco/v86y2024ics1043951x24000889.html

Estimation of industry-level basic digital capital services in China: A variable depreciation rate estimation method based on DSGE

Author

Listed:
  • Liu, Yunxia
  • Li, Fuping

Abstract

Accurately measuring the input of digital capital is of great significance for understanding the development pattern of China's digital economy, nurturing new quality productivity, and achieving high-quality development. However, existing representative studies often assume a constant depreciation rate for capital goods, which does not align with reality. In this paper, we address this limitation by introducing dynamic stochastic general equilibrium (DSGE) model that estimates the variable depreciation rate for each capital good. By setting the depreciation rate as a function of capital maintenance expenditures and utilization rates, we provide a more realistic approach. The empirical results obtained through Monte Carlo simulation demonstrate that the trend of depreciation rates for all types of capital goods aligns with China's economic development. Additionally, we find that investment-specific technology shock plays a significant role in affecting changes in the depreciation rates of capital goods. This shock leads to an increase in capital utilization rates and a decrease in capital maintenance expenditures, resulting in higher depreciation rates. Notably, the depreciation rate of basic digital capital is more sensitive to exogenous shock compared to non-digital capital. Furthermore, the paper estimates the basic digital capital service of 19 industries in China from 1981 to 2020. The results indicate a steady increase in the services provided by basic digital capital, with particularly rapid growth observed in industries such as information transmission, software and information technology services, and the financial sector. When comparing our estimation results with those of representative literature, we find that the national-level productive capital stock and the basic digital capital services estimated using our methodology closely align with existing literature. This validation confirms the effectiveness of our methodology and the reliability of the estimated industry-level basic digital capital services.

Suggested Citation

  • Liu, Yunxia & Li, Fuping, 2024. "Estimation of industry-level basic digital capital services in China: A variable depreciation rate estimation method based on DSGE," China Economic Review, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:chieco:v:86:y:2024:i:c:s1043951x24000889
    DOI: 10.1016/j.chieco.2024.102199
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1043951X24000889
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chieco.2024.102199?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Hongsheng & Liu, Qingqing & Wei, Yueling, 2023. "Digital product imports and export product quality: Firm-level evidence from China," China Economic Review, Elsevier, vol. 79(C).
    2. Albonico, Alice & Kalyvitis, Sarantis & Pappa, Evi, 2014. "Capital maintenance and depreciation over the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 273-286.
    3. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    4. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 1997. "Long-Run Implications of Investment-Specific Technological Change," American Economic Review, American Economic Association, vol. 87(3), pages 342-362, June.
    5. WU, Jidong & LI, Ning & SHI, Peijun, 2014. "Benchmark wealth capital stock estimations across China's 344 prefectures: 1978 to 2012," China Economic Review, Elsevier, vol. 31(C), pages 288-302.
    6. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2005. "Productivity, Volume 3: Information Technology and the American Growth Resurgence," MIT Press Books, The MIT Press, edition 1, volume 3, number 0262101114, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hou, Yao & Huang, Jinglei & Xie, Danxia & Zhou, Weidi, 2025. "The limits to growth in the AI-driven economy," China Economic Review, Elsevier, vol. 94(PA).
    2. Chen, Jinrui & Zhang, Yichang, 2025. "Substantive change or strategic response? Digital industrial convergence policy and urban green innovation," Innovation and Green Development, Elsevier, vol. 4(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Belousova, Irina, 2017. "The role of endogenous capital depreciation rate in Dynamic Stochastic General Equilibrium models: Evidence from Canada," MPRA Paper 102036, University Library of Munich, Germany.
    2. Elstner, Steffen & Feld, Lars P. & Schmidt, Christoph M., 2018. "The German productivity paradox: Facts and explanations," Ruhr Economic Papers 767, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Paul Welfens, 2014. "Issues of modern macroeconomics: new post-crisis perspectives on the world economy," International Economics and Economic Policy, Springer, vol. 11(4), pages 481-527, December.
    4. Raouf Boucekkine & Bruno de Oliveira Cruz, 2015. "Technological Progress and Investment: A Non-Technical Survey," AMSE Working Papers 1519, Aix-Marseille School of Economics, France.
    5. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2009. "Sources of the Great Moderation: shocks, frictions, or monetary policy?," FRB Atlanta Working Paper 2009-03, Federal Reserve Bank of Atlanta.
    6. Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    7. 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.
    8. Martin Andreasen, 2011. "An estimated DSGE model: explaining variation in term premia," Bank of England working papers 441, Bank of England.
    9. Martin Møller Andreasen, 2008. "Explaining Macroeconomic and Term Structure Dynamics Jointly in a Non-linear DSGE Model," CREATES Research Papers 2008-43, Department of Economics and Business Economics, Aarhus University.
    10. Alban Moura & Olivier Pierrard, 2024. "Bayesian Evaluation of DSGE Models with Housing and Collateral Effects," Annals of Economics and Statistics, GENES, issue 155, pages 91-124.
    11. Moura, Alban, 2021. "Are neutral and investment-specific technology shocks correlated?," European Economic Review, Elsevier, vol. 139(C).
    12. Hansen, G.D. & Ohanian, L.E., 2016. "Neoclassical Models in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2043-2130, Elsevier.
    13. Zheng Liu & John Fernald & Susanto Basu, 2012. "Technology Shocks in a Two-Sector DSGE Model," 2012 Meeting Papers 1017, Society for Economic Dynamics.
    14. Justiniano, Alejandro & Primiceri, Giorgio E. & Tambalotti, Andrea, 2010. "Investment shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 132-145, March.
    15. Fabio Milani & Sung Ho Park, 2019. "Expectations and Macro-Housing Interactions in a Small Open Economy: Evidence from Korea," Open Economies Review, Springer, vol. 30(2), pages 375-402, April.
    16. Leeper, Eric M. & Plante, Michael & Traum, Nora, 2010. "Dynamics of fiscal financing in the United States," Journal of Econometrics, Elsevier, vol. 156(2), pages 304-321, June.
    17. Jacob, Punnoose & Peersman, Gert, 2013. "Dissecting the dynamics of the US trade balance in an estimated equilibrium model," Journal of International Economics, Elsevier, vol. 90(2), pages 302-315.
    18. L. Rachel Ngai & Roberto M. Samaniego, 2006. "An R&D-Based Model of Multi-Sector Growth," CEP Discussion Papers dp0762, Centre for Economic Performance, LSE.
    19. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    20. Pedro Brinca & João Ricardo Costa Filho & Francesca Loria, 2024. "Business cycle accounting: What have we learned so far?," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1276-1316, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chieco:v:86:y:2024:i:c:s1043951x24000889. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/chieco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.